scholarly journals Investigating the factors affecting physics performance of Indonesian students by using a multilevel model based on TIMSS 2011 dataset

2021 ◽  
Author(s):  
Khusaini ◽  
I. Gusti Ngurah Darmawan
Keyword(s):  
Multilevel Model ◽  
Factors Affecting ◽  
Model Based ◽  
Physics Performance

scholarly journals Factors Affecting Radiation Dose in Computed Tomography Angiograms for Pulmonary Embolism: A Retrospective Cohort Study

2020 ◽  
Vol 10 ◽  
pp. 74
Author(s):  
Prashant Nagpal ◽  
Sarv Priya ◽  
Ali Eskandari ◽  
Aidan Mullan ◽  
Tanya Aggarwal ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Pulmonary Embolism ◽  
Radiation Dose ◽  
Care Center ◽  
Tertiary Care ◽  
Multivariate Logistic Regression Analysis ◽  
Factors Affecting ◽  
Model Based ◽  
Pulmonary Angiogram ◽  
The Mean

Objectives: Computed tomography pulmonary angiogram (CTPA) is one of the most commonly ordered and frequently overused tests. The purpose of this study was to evaluate the mean radiation dose to patients getting CTPA and to identify factors that are associated with higher dose. Material and Methods: This institutionally approved retrospective study included all patients who had a CTPA to rule out acute pulmonary embolism between 2016 and 2018 in a tertiary care center. Patient data (age, sex, body mass index [BMI], and patient location), CT scanner type, image reconstruction methodology, and radiation dose parameters (dose-length product [DLP]) were recorded. Effective dose estimates were obtained by multiplying DLP by conversion coefficient (0.014 mSv•mGy−1•cm−1). Multivariate logistic regression analysis was performed to determine the factors affecting the radiation dose. Results: There were 2342 patients (1099 men and 1243 women) with a mean age of 58.1 years (range 0.2–104.4 years) and BMI of 31.3 kg/m2 (range 12–91.5 kg/m2). The mean effective radiation dose was 5.512 mSv (median – 4.27 mSv; range 0.1–43.0 mSv). Patient factors, including BMI >25 kg/m2, male sex, age >18 years, and intensive care unit (ICU) location, were associated with significantly higher dose (P < 0.05). CT scanning using third generation dual-source scanner with model-based iterative reconstruction (IR) had significantly lower dose (mean: 4.90 mSv) versus single-source (64-slice) scanner with filtered back projection (mean: 9.29 mSv, P < 0.001). Conclusion: Patients with high BMI and ICU referrals are associated with high CT radiation dose. They are most likely to benefit by scanning on newer generation scanner using advance model-based IR techniques.

scholarly journals An Interaction Model for Resource Implement Complexity Based on Risk and Number of Annual Moves

2008 ◽  
Vol 73 (4) ◽  
pp. 599-625 ◽  
Author(s):  
Dwight Read
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Interaction Model ◽  
Growing Season ◽  
Food Resources ◽  
Factors Affecting ◽  
Model Based ◽  
Proxy Measure

Different hypotheses identifying factors affecting the complexity of implements used to obtain food resources by hunter-gatherer groups are assessed with regression analysis. A regression model based on interaction between growing season as a proxy measure for risk and number of yearly moves fits data on the complexity of implements for 20 hunter-gatherer groups. The interaction model leads to a division of hunter-gatherer groups into two subgroups that correspond to collector vs. forager strategies for procuring resources. Implications of the interaction model for the evolution of complex implements are discussed.

Factors affecting future demand for electric vehicles: A model based study

2012 ◽  
Vol 20 ◽  
pp. 62-74 ◽  
Author(s):  
Simon Shepherd ◽  
Peter Bonsall ◽  
Gillian Harrison
Keyword(s):  
Electric Vehicles ◽  
Factors Affecting ◽  
Model Based ◽  
Future Demand

scholarly journals Information dissemination model based on multi-dimensional node influence in social networks

2020 ◽  
Author(s):  
Haiming Wu ◽  
Ruigang Wang ◽  
Lixia Jia ◽  
Likui Feng ◽  
Xu Zhou
Keyword(s):  
Social Networks ◽  
Epidemic Model ◽  
Information Dissemination ◽  
State Transition ◽  
User Interaction ◽  
Multiple Linear Regression Model ◽  
Three Dimensions ◽  
Social Recommendation ◽  
Factors Affecting ◽  
Model Based

Abstract Social network has gradually become the mainstream way for people to obtain and interact with information. The study on the law of information dissemination in social networks is of great significance to enterprise marketing, public opinion control and social recommendation. This paper puts forward a method that use multi-dimensional node influence and epidemic model to illustrate the causes and rules of information dissemination in social networks. Firstly, based on the multiple linear regression model, a measurement method of node influence is proposed from three dimensions: topology, user interaction behavior and information content. Then, taking the node influence as the cause of state transition, the information dissemination model based on the epidemic model is constructed, and the multidimensional factors affecting the information dissemination are analyzed. Meanwhile, the information dissemination trend in social networks is described.

scholarly journals A Multilevel Model Approach for Assessing the Effects of House and Neighborhood Characteristics on Housing Vacancy: A Case of Daegu, South Korea

2019 ◽  
Vol 11 (9) ◽  
pp. 2515
Author(s):  
Jeong-Il Park
Keyword(s):  
South Korea ◽  
Physical Environment ◽  
Multilevel Model ◽  
Hot Spot ◽  
Population Decline ◽  
Single Family ◽  
Factors Affecting ◽  
Clustering Pattern ◽  
Housing Vacancy ◽  
Neighborhood Level

Previous studies on housing vacancy mostly focused on variables representing regional characteristics while overlooking the characteristics of individual houses. This is due to the limitations of available data. Using the house-level Housing Vacancy Database, this study aims to identify the spatial clustering pattern of vacant houses by examining single-family houses in Daegu, South Korea, and analyze the factors affecting housing vacancy. The Housing Vacancy Database built in this study provides accurate location information of vacant houses, making it possible to analyze the clustering pattern of vacant houses in a more detailed spatial unit. Furthermore, the Housing Vacancy Database considered various physical and neighborhood factors at the house level. The result of hot spot analysis showed that vacant houses were spatially concentrated in the city center. As a result of analyzing the factors affecting housing vacancy at the house level and neighborhood level using a multilevel model, it was found that the physical environment characteristics of individual houses were key factors affecting housing vacancy. Additionally, the probability of housing vacancy tended to increase when the land prices were higher, the houses were located in redevelopment zones, and there were more neighboring vacant houses nearby. Meanwhile, population decline and the ratio of old houses were the only significant variables at the neighborhood level. Thus, this study addresses that policies are needed to improve housing and physical environment characteristics that contribute to housing vacancy.

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