scholarly journals Evaluation of the Operation Process of Medical Equipment to Enhance Ergonomic Reliability Based on FRAM–Moran’s I and CREAM

2021 ◽  
Vol 12 (1) ◽  
pp. 200
Author(s):  
Xin Liu ◽  
Zheng Liu ◽  
Kang-Chao Lin ◽  
Zhi-Lin Huang ◽  
Ming-Yu Ling ◽  
...  
Keyword(s):  
Individual Differences ◽  
Medical Equipment ◽  
Evaluation Method ◽  
Moran’S I ◽  
Analysis Method ◽  
Moran's I ◽  
Operation Process ◽  
Order Preference ◽  
The Individual ◽  
The Impact

To improve the ergonomic reliability of medical equipment design during the operation process, a method for evaluating the operating procedure of a medical equipment interface according to functional resonance analysis method (FRAM)-Moran’s I and cognitive reliability and error analysis method (CREAM) is proposed in this study. The novelty of this research is to analyze the ergonomic reliability of medical equipment in a more systematic manner and to minimize the impact of human subjectivity and individual differences on the evaluation results of the operation process. To solve the calculation problem of functional resonance in FRAM and to make the evaluation results more objective, Moran’s I was introduced to quantify the deviation degree caused by the individual differences of the subjects. By giving weights based on Moran’s I, the influence of individual differences and subjectivity on the evaluation results can be minimized, to a certain extent. Considering the importance of a special environment, which is not fully considered by the conventional CREAM, the weighting values based on Moran’s I, Delphi survey, and technique for order preference by similarity to an ideal solution (TOPSIS) were adopted to assign weights to common performance conditions (CPCs) in CREAM. The optimal design scheme was selected more objectively than in the conventional method. The validity and practicability of this operation process evaluation method was verified by a statistical method based on ergonomic reliability experiments.

Predictors of Positive Psychological Capital: An Attempt Among the Teacher Communities in Rural Jharkhand, India

2021 ◽  
pp. 0258042X2199101
Author(s):  
Mukti Clarence ◽  
Viju P. D. ◽  
Lalatendu Kesari Jena ◽  
Tony Sam George
Keyword(s):  
Individual Differences ◽  
Organizational Support ◽  
Psychological Capital ◽  
Contextual Factors ◽  
Meaningful Work ◽  
Equation Modeling ◽  
School Teachers ◽  
Positive Psychological Capital ◽  
The Individual ◽  
The Impact

In the recent times, researchers have shown an increased interest in positive psychological capital (PsyCap). However, it is acknowledged that due to the limited number of studies conducted on the antecedents of psychological capital, there is a lack of sufficient data for conclusively proving the antecedents of PsyCap. Consequently, this article aims to explore the potential antecedents of PsyCap as a reliable source of data in the context of rural school teachers. The focus is to investigate both the individual differences and the contextual factors as desirable variables that constitute PsyCap among the school teachers of rural Jharkhand, India. Samples of 1,120 respondents from different rural schools were collected and analysed with Structural Equation Modeling (AMOS 20.0). The findings of the study explained that both the individual differences ( proactive personality and emotional intelligence) and the contextual factors ( perceived organizational support, servant leadership and meaningful work) have a positive relationship with PsyCap. The impact of PsyCap on teacher performance can form the basis for further research on the subject. JEL Codes: M12, M53

scholarly journals Investigation of Impact of Aggregate Coating by Bitumen on Change of Micro Texture Values

1970 ◽  
Vol 3 (1) ◽  
pp. 52-61
Author(s):  
Zuzana Florkova ◽  
Jana Pastorkova ◽  
Matus Farbak ◽  
Zuzana Kolkova ◽  
Peter Hrabovsky
Keyword(s):  
Asphalt Pavement ◽  
Asphalt Mixture ◽  
Asphalt Mixtures ◽  
Point Of View ◽  
Skid Resistance ◽  
Analysis Method ◽  
Texture Change ◽  
Bitumen Content ◽  
The Individual ◽  
The Impact

Asphalt pavement micro texture values primarily depend on aggregate properties used in asphalt pavement mixture and by aggregate surfaces is secured the basic contact medium with vehicle tires. It often happens that new asphalt surfaces have not required skid resistance properties and is needed a certain period of time to eliminate film of bitumen binder which is coating the aggregate grain on the surface of pavement by action of vehicles. In most cases, the investigation of the aggregate micro texture impact on the pavement skid resistance properties is carried out under laboratory conditions and generally relates only to measurements on natural aggregate samples (without bitumen). However, due to coating of aggregate by bitumen binder, valleys between the individual peaks of aggregate are filled. Obviously, it can be supposed that the usage of high amount of bitumen content can leads to decreasing of aggregate micro texture values. From this point of view, it can be expected that change in micro texture values depends on the content of binder in the asphalt mixture. Particular aggregate grains were taken from asphalt mixtures samples (AC 8, AC 11 and SMA 11) produced in the laboratory, in order to determine the impact of aggregate coating by bitumen binder on micro texture change. Each usage asphalt mixture was produced with three different bitumen binder contents. Digital image analysis method was used for subsequent evaluation. Changes in the micro texture values depending on the amount of used bitumen binder and also on the calculated theoretical bitumen film thickness are investigated in the conclusion.

Understanding the Dark Side of Costly Punishment: The Impact of Individual Differences in Everyday Sadism and Existential Threat

2015 ◽  
Vol 29 (4) ◽  
pp. 498-505 ◽  
Author(s):  
Stefan Pfattheicher ◽  
Simon Schindler
Keyword(s):  
Individual Differences ◽  
Empirical Support ◽  
Self Esteem ◽  
Situational Factors ◽  
Dark Side ◽  
Personality Psychology ◽  
Costly Punishment ◽  
Basic Characteristics ◽  
The Individual ◽  
The Impact

In public goods situations, a specific destructive behaviour reliably emerges when individuals face the possibility of costly punishing others: antisocial punishment, that is, costly punishing cooperative individuals. So far, however, little is known about the individual differences and situational factors that are associated with the dark side of costly punishment. This research deals with this shortcoming. We argue that antisocial punishment reflects the basic characteristics of sadism, namely, aggressive behaviour to dominate and to harm other individuals. We further argue that antisocial punishment may reflect a type of behaviour that allows for the maintenance of self–esteem (through aggressively dominating others). Therefore, we expect that individuals who report a disposition for everyday sadism are particularly likely to engage in antisocial punishment when their self has been threatened (by thinking about one's own death). In a study ( N = 99), we found empirical support for this assumption. The present research contributes to a better understanding of antisocial punishment and suggests that sadistic tendencies play a crucial role, especially when the self is (existentially) threatened. Copyright © 2015 European Association of Personality Psychology

scholarly journals Can health service equity alleviate the health expenditure poverty of Chinese patients? Evidence from the CFPS and China health statistics yearbook

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shaoliang Tang ◽  
Ling Yao ◽  
Chaoyu Ye ◽  
Zhengjun Li ◽  
Jing Yuan ◽  
...  
Keyword(s):  
Health Service ◽  
Health Expenditure ◽  
Negative Impact ◽  
Medical Insurance ◽  
Moran’S I ◽  
Chinese Patients ◽  
Index Formula ◽  
Moran's I ◽  
Per Capita ◽  
The Impact

Abstract Objectives To comprehend the relationship between various indicators of health service equity and patients’ health expenditure poverty in different regions of China, identify areas where equity in health service is lacking and provide ideas for improving patients’ health expenditure poverty. Method Data from China Family Panel Studies (CFPS) in 2018 and the HFGT index formula were used to calculate the health expenditure poverty index of each province. Moreover, Global Moran’s I and Local Moran’s I test are applied to measure whether there is spatial aggregation of health expenditure poverty. Finally, an elastic net regression model is established to analyze the impact of health service equity on health expenditure poverty, with the breadth of health expenditure poverty as the dependent variable and health service equity as the independent variable. Results In the developed eastern provinces of China, the breadth of health expenditure poverty is relatively low. There is a significant positive spatial agglomeration. “Primary medical and health institutions per 1,000 population”, “rural doctors and health workers per 1,000 population”, “beds in primary medical institutions per 1,000 population”, “proportion of government health expenditure” and “number of times to participate in medical insurance (be aided) per 1,000 population” have a positive impact on health expenditure poverty. “Number of health examinations per capita” and “total health expenditure per capita” have a negative impact on health expenditure poverty. Both effects passed the significance test. Conclusion To enhance the fairness of health resource allocation in China and to alleviate health expenditure poverty, China should rationally plan the allocation of health resources at the grassroots level, strengthen the implementation of hierarchical diagnosis and treatment and encourage the investment in business medical insurance industry. Meanwhile, it is necessary to increase the intensity of medical assistance and enrich financing methods. All medical expenses of the poorest should be covered by the government.

scholarly journals Measuring The Impact of Spatial Perturbations on The Relationship Between Data Privacy and Validity of Descriptive Statistics

2020 ◽  
Author(s):  
Kelly Broen ◽  
Rob Trangucci ◽  
Jon Zelner
Keyword(s):  
Spatial Statistics ◽  
Spatial Patterns ◽  
Spatial Data ◽  
Data Privacy ◽  
Perturbation Methods ◽  
Descriptive Statistics ◽  
Moran’S I ◽  
Mortality Data ◽  
Moran's I ◽  
The Impact

Abstract Background: Like many scientific fields, epidemiology is addressing issues of research reproducibility. Spatial epidemiology, which often uses the inherently identifiable variable of participant address, must balance reproducibility with participant privacy. In this study, we assess the impact of several different data perturbation methods on key spatial statistics and patient privacy. Methods: We analyzed the impact of perturbation on spatial patterns in the full set of address- level mortality data from Lawrence, MA during the period from 1911-1913. The original death locations were perturbed using seven different published approaches to stochastic and deterministic spatial data anonymization. Key spatial descriptive statistics were calculated for each perturbation, including changes in spatial pattern center, Global Moran’s I, Local Moran’s I, distance to the k-th nearest neighbors, and the L-function (a normalized form of Ripley’s K). A spatially adapted form of k-anonymity was used to measure the privacy protection conferred by each method, and the its compliance with HIPAA privacy standards. Results: Random perturbation at 50 meters, donut masking between 5 and 50 meters, and Voronoi masking maintain the validity of descriptive spatial statistics better than other perturbations. Grid center masking with both 100x100 and 250x250 meter cells led to large changes in descriptive spatial statistics. None of the perturbation methods adhered to the HIPAA standard that all points have a k-anonymity > 10. All other perturbation methods employed had at least 265 points, or over 6%, not adhering to the HIPAA standard. Conclusions: Using the set of published perturbation methods applied in this analysis, HIPAA- compliant de-identification was not compatible with maintaining key spatial patterns as measured by our chosen summary statistics. Further research should investigate alternate methods to balancing tradeoffs between spatial data privacy and preservation of key patterns in public health data that are of scientific and medical importance.

scholarly journals Assessment of the Impact of a Motorway on Content andSpatial Distribution of Mercury in Adjacent Agricultural Soils

Minerals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1221
Author(s):  
Hanna Jaworska ◽  
Joanna Klimek
Keyword(s):  
Crop Protection ◽  
Spatial Relationship ◽  
Mercury Content ◽  
Test Point ◽  
Moran’S I ◽  
Arable Soils ◽  
Weighted Interpolation ◽  
Moran's I ◽  
Noise Barrier ◽  
The Impact

The distribution of Hg in the vicinity of roads is probably not exclusively dependent on car emissions, but also on the presence of other point or diffuse sources of Hg emissions located from metres to several km away. The source of mercury in urbanised areas is pollution derived from the burning of fuels and industrial and transport waste, while in agricultural areas, it is constituent in mineral fertilisers and crop protection products. The research objective was to evaluate the content and spatial distribution of mercury in arable soils adjacent to the A1 motorway in Poland. The research material consisted of 40 soil samples taken from 20 test points on four transects at distances of 5, 10, 25 and 50 m from a noise barrier and in the direction of an arable field, and 10 m from the noise barrier in the direction of the motorway. Total mercury content was determined by atomic absorption spectrometry using an AMA 254 analyser. The spatial relationship between adjacent observations of variables was assessed using Moran’s I overall autocorrelation coefficient. Probability maps of mercury distribution in the field and pollution indicators were elaborated in ArcGIS 10.4.1. using Inverse Distance Weighted interpolation. Analysis of the spatial correlation of Moran’s I showed a lack of spatial dependence between tested points, which may evidence that the motorway does not affect mercury contents in the soil. The elevated mercury content at a single test point may indicate a random event unrelated to the motorway’s operation.

scholarly journals Measuring the impact of spatial perturbations on the relationship between data privacy and validity of descriptive statistics

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Kelly Broen ◽  
Rob Trangucci ◽  
Jon Zelner
Keyword(s):  
Spatial Statistics ◽  
Spatial Patterns ◽  
Spatial Data ◽  
Data Privacy ◽  
Perturbation Methods ◽  
Descriptive Statistics ◽  
Moran’S I ◽  
Mortality Data ◽  
Moran's I ◽  
The Impact

Abstract Background Like many scientific fields, epidemiology is addressing issues of research reproducibility. Spatial epidemiology, which often uses the inherently identifiable variable of participant address, must balance reproducibility with participant privacy. In this study, we assess the impact of several different data perturbation methods on key spatial statistics and patient privacy. Methods We analyzed the impact of perturbation on spatial patterns in the full set of address-level mortality data from Lawrence, MA during the period from 1911 to 1913. The original death locations were perturbed using seven different published approaches to stochastic and deterministic spatial data anonymization. Key spatial descriptive statistics were calculated for each perturbation, including changes in spatial pattern center, Global Moran’s I, Local Moran’s I, distance to the k-th nearest neighbors, and the L-function (a normalized form of Ripley’s K). A spatially adapted form of k-anonymity was used to measure the privacy protection conferred by each method, and its compliance with HIPAA and GDPR privacy standards. Results Random perturbation at 50 m, donut masking between 5 and 50 m, and Voronoi masking maintain the validity of descriptive spatial statistics better than other perturbations. Grid center masking with both 100 × 100 and 250 × 250 m cells led to large changes in descriptive spatial statistics. None of the perturbation methods adhered to the HIPAA standard that all points have a k-anonymity > 10. All other perturbation methods employed had at least 265 points, or over 6%, not adhering to the HIPAA standard. Conclusions Using the set of published perturbation methods applied in this analysis, HIPAA and GDPR compliant de-identification was not compatible with maintaining key spatial patterns as measured by our chosen summary statistics. Further research should investigate alternate methods to balancing tradeoffs between spatial data privacy and preservation of key patterns in public health data that are of scientific and medical importance.

Analisis Moran’s I, Geary’s C, dan Getis-Ord G pada Penerapan Jumlah Penderita Kusta di Kabupaten Gowa

2020 ◽  
Vol 2 (2) ◽  
pp. 151
Author(s):  
S. Sukarna ◽  
Wahidah Sanusi ◽  
Hafilah Hardiono
Keyword(s):  
Infectious Disease ◽  
Spatial Analysis ◽  
Spatial Autocorrelation ◽  
Spatial Patterns ◽  
Moran’S I ◽  
Analysis Method ◽  
Moran's I ◽  
Surrounding Areas ◽  
Geary’S C ◽  
Quadrat Analysis

Analisis spasial merupakan salah satu metode yang sering digunakan dalam melihat pola penyebaran penyakit menular. Penyakit Kusta atau lepra merupakan penyakit menular kronis yang disebabkan oleh bakteri Mycrobacterium Leprae yang penyebarannya melalui droplet. Penelitian ini bertujuan untuk mengetahui pola spasial pada Kusta dengan menggunakan metode Quadrat Analysis, untuk mengetahui ada atau tidaknya autokorelasi spasial antar daerah dengan menggunakan Moran’s I, Geary’s C, Getis-Ord G, dan pemetaan penyebaran penyakit Kusta di Kabupaten Gowa. Pada penelitian ini diperoleh bahwa pola spasial penyebaran penyakit Kusta pada Tahun 2016 dan 2017 di Kabupaten Gowa bersifat mengelompok (clustered). Pada Tahun 2016 terdapat autokorelasi spasial dengan pengujian Moran’s I  dan Geary’s C, sedangkan pengujian Getis-Ord G tidak terdapat autokorelasi spasial antar daerah. Pada Tahun 2017 tidak terdapat autokorelasi spasial antar daerah dengan menggunakan ke tiga pengujian tersebut. Pada Tahun 2016 daerah yang rawan adalah Barombong, daerah yang harus berhati-hati dengan daerah sekitarnya adalah Bontonompo dan daerah yang termasuk kategori aman adalah Tompobulu. Sedangkan pada tahun 2017 daerah yang rawan terhadap penyakit Kusta adalah Bajeng dan Manuju.Kata kunci : Moran’s I, Geary’s C, Getis-Ord G, Moran Scatterplot, Kusta Spatial analysis is one of the methods that is often used to observe spreading pattern of infectious diseases. Leprosy is a chronic infectious disease caused by bacterium Mycrobacterium Leprae which spreads through droplets. This study aims to determine the spatial pattern of leprosy using the Quadrat Analysis method, to determine whether there is spatial autocorrelation between regions using Moran's I, Geary’s C, Getis-Ord G, and mapping the spread of leprosy in Gowa Regency. In this study it was found that the spatial patterns of the spread of leprosy in 2016 and 2017 in Gowa Regency was clustered. In 2016 there were spatial autocorrelations with the tests of Moran's I and Geary's C, while the testing of Getis-Ord G did not have spatial autocorrelation between regions. In 2017 there is no spatial autocorrelation between regions using the three tests. In 2016 the vulnerable areas was Barombong, the area that had to be careful with the surrounding areas was Bontonompo and the area included in the safe category was Tompobulu. Whereas in 2017 areas prone to leprosy were Bajeng and Manuju.Keywords : Moran's I, Geary's C, Getis-Ord G, Moran Scatterplot, Leprosy

scholarly journals The Impact of Inter-City Traffic Restriction on COVID-19 Transmission from Spatial Econometric Perspective

2021 ◽  
Vol 33 (5) ◽  
pp. 705-716
Author(s):  
Xijin Lu ◽  
Changxi Ma
Keyword(s):  
Spatial Correlation ◽  
Goodness Of Fit ◽  
Ordinary Least Squares ◽  
Hubei Province ◽  
Error Model ◽  
Moran’S I ◽  
Spatial Error ◽  
Moran's I ◽  
Spatial Lag ◽  
The Impact

The aim of this paper is to conduct a spatial correlation study of virus transmission in the Hubei province, China. The number of confirmed COVID-19 cases released by the National Health and Construction Commission, the traffic flow data provided by Baidu migration, and the current situation of Wuhan intercity traffic were collected. The Moran’s I test shows that there is a positive spatial correlation between the 17 cities in the Hubei province. The result of Moran’s I test also shows that four different policies to restrict inter-city traffic can be issued for the four types of cities. The ordinary least squares regression, spatial lag model, spatial error model, and spatial lag error model were built. Based on the analysis of the spatial lag error model, whose goodness of fit is the highest among the four models, it can be concluded that the speed of COVID-19 spread within a certain region is not only related to the current infection itself but also associated with the scale of the infection in the surrounding area. Thus, the spill-over effect of the COVID-19 is also presented. This paper bridges inter-city traffic and spatial economics, provides a theoretical contribution, and verifies the necessity of a lockdown from an empirical point of view.

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