A Method for Assessing the Fairness of Health Resource Allocation Based on Geographical Grid

Han, Jin Woo; Jiang, Wenhao; Jin, Shi; Sun, Xin; Peng, Jin Shuan; Li, Haibo

doi:10.32604/cmc.2019.07447

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…Third, based on the perspective of medical facility distribution [8]. Han et al used maximum likelihood estimation to measure the fairness of health resource allocation in the target area of the grid [9]. Ji and Zhang used standard deviation ellipse, kernel density estimation, and spatial hot spot analysis to analyze the spatial distribution of medical and nursing care resources in Beijing [10].…”

Section: Literature Review 21 Spatial Distribution Of Pension Institu...mentioning

confidence: 99%

Spatial Distribution of Pension Institutions in Shanghai Based on the Perspective of Wisdom Grade

Tian

2023

IJGI

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The academic research on the spatial distribution of pension institutions is mostly from the perspective of constructing or improving spatial analysis methods. It is not considered that with the development of social science and technology, the facilities and services of elderly care institutions will develop in the direction of intelligence. Exploring the intelligence level and spatial distribution of Shanghai’s elderly care institutions has important practical significance for improving and optimizing the service facilities and resource allocation of Shanghai’s pension institutions. The spatial scale and cluster distribution of pension institutions in Shanghai are described by means of standard deviation ellipse, kernel density analysis, spatial autocorrelation analysis, and spatial hotspot analysis. The Gini coefficient of intelligent bed is proposed to describe the comprehensive allocation of resources of pension institutions. Additionally, correlation analysis is used to explore the spatial fairness distribution of pension institutions in Shanghai. The results show that the development of pension institutions in various districts of Shanghai is uneven; the distribution of pension institutions is concentrated in the central urban area; the intelligent facilities, service resources, and the number of beds of pension institutions in the suburbs are better than those in the central urban area. Based on the analysis results, policy suggestions are put forward, such as optimizing the allocation of bed resources in pension institutions and focusing on building a more equitable and rationally structured smart pension institution.

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Section: Literature Review 21 Spatial Distribution Of Pension Institu...mentioning

confidence: 99%

Spatial Distribution of Pension Institutions in Shanghai Based on the Perspective of Wisdom Grade

Tian

2023

IJGI

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“…In solving the problem of dynamic resource allocation, the literature proposed Service based system (SBS) to apply dynamic resource allocation method [11]. When user demand changes dynamically, the application load in SBS will be different at different moments.…”

Section: Related Workmentioning

confidence: 99%

Fair and Stable Matching Virtual Machine Resource Allocation Method

Dai¹,

He²,

Sun³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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In order to unify the management and scheduling of cloud resources, cloud platforms use virtualization technology to re-integrate multiple computing resources in the cloud and build virtual units on physical machines to achieve dynamic provisioning of resources by configuring virtual units of various sizes. Therefore, how to reasonably determine the mapping relationship between virtual units and physical machines is an important research topic for cloud resource scheduling. In this paper, we propose a fair cloud virtual machine resource allocation method of using the stable matching theory. Our allocation method considers the allocation of resources from both user's demand and cloud computing resource provider's request. When multiple users apply for resources, firstly select a user by user priority, and then deal with this user's task. Because the user priority is dynamic, so as to avoid a user's long-term share of resources. This strategy makes user task scheduling is relatively fair. On the basis of weighing the fair allocation of user resources, the stable matching between physical machines and virtual machines is achieved. Our simulation experiments especially given that the main focus of the paper is not to develop a very novel algorithm, but to demonstrate our virtual machine resource allocation method, which effectively improves the average utilization rate of computing resources and reduces the operating costs of cloud providers.

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“…It was difficult for us to obtain the data for the population and economy of small areas due to various restrictions. Han et al [21] proposed a model using maximum likelihood estimation to build a population assessment model based on a hot keyword crawler. Our experiment used this population assessment model to calculate the population and economic data of each grid in Hunan Province through an estimate based on the number of keywords in each grid.…”

Section: Build the Neural Networkmentioning

confidence: 99%

A Rasterized Lightning Disaster Risk Method for Imbalanced Sets Using Neural Network

Zhang¹,

Han²,

Yuan³

et al. 2020

Computers, Materials &Amp; Continua

Self Cite

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Over the past 10 years, lightning disaster has caused a large number of casualties and considerable economic loss worldwide. Lightning poses a huge threat to various industries. In an attempt to reduce the risk of lightning-caused disaster, many scholars have carried out in-depth research on lightning. However, these studies focus primarily on the lightning itself and other meteorological elements are ignored. In addition, the methods for assessing the risk of lightning disaster fail to give detailed attention to regional features (lightning disaster risk). This paper proposes a grid-based risk assessment method based on data from multiple sources. First, this paper considers the impact of lightning, the population density, the economy, and geographical environment data on the occurrence of lightning disasters; Second, this paper solves the problem of imbalanced lightning disaster data in geographic grid samples based on the K-means clustering algorithm; Third, the method calculates the feature of lightning disaster in each small field with the help of neural network structure, and the calculation results are then visually reflected in a zoning map by the Jenks natural breaks algorithm. The experimental results show that our method can solve the problem of imbalanced lightning disaster data, and offer 81% accuracy in lightning disaster risk assessment.

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A Method for Assessing the Fairness of Health Resource Allocation Based on Geographical Grid

Cited by 6 publications

References 6 publications

Spatial Distribution of Pension Institutions in Shanghai Based on the Perspective of Wisdom Grade

Spatial Distribution of Pension Institutions in Shanghai Based on the Perspective of Wisdom Grade

Fair and Stable Matching Virtual Machine Resource Allocation Method

A Rasterized Lightning Disaster Risk Method for Imbalanced Sets Using Neural Network

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