Time series analysis and spatial distribution map of aggregate risk index due to tropospheric NO2 and O3 based on satellite observation

2022 ◽  
Vol 304 ◽  
pp. 114202
Author(s):  
Neda Shojaei Baghini ◽  
Samereh Falahatkar ◽  
Mohammad Sadegh Hassanvand
Keyword(s):  
Time Series ◽  
Spatial Distribution ◽  
Time Series Analysis ◽  
Risk Index ◽  
Satellite Observation ◽  
Distribution Map ◽  
Series Analysis ◽  
Aggregate Risk ◽  
Tropospheric No2 ◽  
Spatial Distribution Map

scholarly journals Flood risk spatial index analysis in the coastal Pekalongan, Central Java, Indonesia

2020 ◽  
Vol 202 ◽  
pp. 06028
Author(s):  
Ratna Mustika Anindita ◽  
Indah Susilowati ◽  
Fuad Muhammad
Keyword(s):  
Spatial Distribution ◽  
Flood Risk ◽  
Risk Index ◽  
Spatial Index ◽  
North Coast ◽  
Distribution Map ◽  
High Level ◽  
Spatial Distribution Map ◽  
Very High ◽  
Level Of Risk

The North coast of Java is increasingly exposed to flood risks due to land subsidence and climate change, resulting in sea-level rise. This paper developed a flood risk spatial index model in the coastal Pekalongan. The model was systematically arranged from various flood risk indicators related to the social, economic, and environment of coastal Pekalongan based on surveys and interviews with the communities and regional governments. These indicators are then integrated into hazard and vulnerability as components of risk. Using the index system method and ArcGIS, the risk index is classified into five levels (very high, high, medium, low, very low) and generated into a flood risk spatial distribution map. We found that the risk in the study area varies between a medium to a very high level of risk. The very high level of risk was located in Tratebang, Pecakaran, and Tegaldowo Village. A risk spatial distribution map can be used to evaluate potential risks and flood mitigation.

Are all the word ranking methods the same?

2021 ◽  
pp. 2150144
Author(s):  
Elham Najafi ◽  
Alireza Valizadeh ◽  
Amir H. Darooneh
Keyword(s):  
Complex System ◽  
Time Series ◽  
Spatial Distribution ◽  
Time Series Analysis ◽  
Complex Networks ◽  
Rank Correlation ◽  
Ranking Methods ◽  
Series Analysis ◽  
Maximum Value

Text as a complex system is commonly studied by various methods, like complex networks or time series analysis, in order to discover its properties. One of the most important properties of each text is its keywords, which are extracted by word ranking methods. There are various methods to rank words of a text. Each method differently ranks words according to their frequency, spatial distribution or other word properties. Here, we aimed to explore how similar various word ranking methods are. For this purpose, we studied the rank correlation of some important word ranking methods for number of sample texts with different subjects and text sizes. We found that by increasing text size the correlation between ranking methods grows. It means that as the text size increases, the associated word ranks calculated by different ranking methods converge. Also, we found out that the rank correlations of word ranking methods approach their maximum value in the case of large enough texts.

scholarly journals The Impact of Weather on Hospitalization due to Pneumonia Among Children in Nghe An from 2014 to 2019

2020 ◽  
Vol 36 (3) ◽  
Author(s):  
Nguyen Chi Sy ◽  
Le Tu Hoang ◽  
Nguyen Thi Trang Nhung ◽  
Vu Thi Hoang Lan ◽  
Tran Minh Dien
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
World Health Organization ◽  
Risk Index ◽  
Daily Temperature ◽  
World Health ◽  
Series Analysis ◽  
Study Results ◽  
Health Organization ◽  
The Impact

This paper studies the impact of weather on the number of under 15-year-old children hospitalized for pneumonia at Nghe An Pediatric Hospital using time series analysis of the data collected from 2014 to 2019. The study was carried out on 45,466 children, most of whom were under 5 years old. The study results show that there was a statistically significant inverse correlation between mean daily temperature and children’s hospitalization for pneumonia while humidity was positively correlated. Specifically, when the average daily temperature increased by 1 degree Celsius, the risk of hospitalization for pneumonia on the same day decreased by 1% (95% CI: 0.3 - 1.7%); whereas when the humidity increased, the risk of hospitalization increased by 14.4% (95% CI: 0.2 - 30.7%) on the day of hospitalization; risk increased by 16.5% (95% CI: 9.5 - 23.9%) one day before hospitalization; and risk increased by 15.2% (95% CI: 8.2 - 22.7%) two days before hospitalization. The results suggest that children are highly sensitive to weather factors, including temperature and humidity; therefore, it is necessary to take measures to protect children against changing weather. Keywords Weather, pneumonia, children, effect. References [1] I. Rudan, et al., Epidemiology and etiology of childhood pneumonia. Bulletin of the World Health Organization 86(5) (2008) 408-416.[2] M. Harris, et al., British Thoracic Society guidelines for the management of community acquired pneumonia in children: update Thorax, 66 (2011) (Suppl 2): p. ii1.[3] Margolis, P. and A. Gadomski, The rational clinical examination. Does this infant have pneumonia? Jama 279(4) (1998) 308-13.[4] World Health Organization, Handbook : IMCI integrated management of childhood illness. 2005, World Health Organization: Geneva.[5] Sönke Kreft, David Eckstein, and Inga Melchior, Global Climate Risk Index 2017, Germanwatch Nord-Süd Initiative e.V.,.[6] Pham Khoi Nguyen, Vietnam's event about sea level rising and climate chang, 2009, Ministry of Natural resources and enviroment.[7] L.M.T. Luong, et al., Effects of temperature on hospitalisation among pre-school children in Hanoi, Vietnam, 26(3) (2019) 2603-2612.[8] D. Phung, et al., Temperature as a risk factor for hospitalisations among young children in the Mekong Delta area, Vietnam. Occupational and Environmental Medicine 72(7) (2015) 529.[9] J. Gao, et al., Impact of ambient humidity on child health: a systematic review. PloS one 9(12) (2014) p. e112508-e112508.[10] Y. Liu, et al., Temporal relationship between hospital admissions for pneumonia and weather conditions in Shanghai, China: a time-series analysis. BMJ Open, 4(7) (2014) p. e004961.[11] T. Egondi, et al., Time-series analysis of weather and mortality patterns in Nairobi's informal settlements. Global health action, 5 (2012) 23-32.[12] Leckebusch, G.C. and A.F. Abdussalam, Climate and socioeconomic influences on interannual variability of cholera in Nigeria. Health Place, 34 (2015) 107-17.        

Dynamical Peculiarities of Concatenational Changes in Functional Cardiovascular Parameters

2018 ◽  
Vol 3 (82) ◽  
Author(s):  
Eurelija Venskaitytė ◽  
Jonas Poderys ◽  
Tadas Česnaitis
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Functional State ◽  
The Body ◽  
Functional Changes ◽  
High Intensity Training ◽  
Series Analysis ◽  
Greco Roman ◽  
St Segment ◽  
Standard Lead

Research  background  and  hypothesis.  Traditional  time  series  analysis  techniques,  which  are  also  used  for the analysis of cardiovascular signals, do not reveal the relationship between the  changes in the indices recorded associated with the multiscale and chaotic structure of the tested object, which allows establishing short-and long-term structural and functional changes.Research aim was to reveal the dynamical peculiarities of interactions of cardiovascular system indices while evaluating the functional state of track-and-field athletes and Greco-Roman wrestlers.Research methods. Twenty two subjects participated in the study, their average age of 23.5 ± 1.7 years. During the study standard 12 lead electrocardiograms (ECG) were recorded. The following ECG parameters were used in the study: duration of RR interval taken from the II standard lead, duration of QRS complex, duration of JT interval and amplitude of ST segment taken from the V standard lead.Research  results.  Significant  differences  were  found  between  inter-parametric  connections  of  ST  segment amplitude and JT interval duration at the pre and post-training testing. Observed changes at different hierarchical levels of the body systems revealed inadequate cardiac metabolic processes, leading to changes in the metabolic rate of the myocardium and reflected in the dynamics of all investigated interactions.Discussion and conclusions. It has been found that peculiarities of the interactions of ECG indices interactions show the exposure of the  functional changes in the body at the onset of the workload. The alterations of the functional state of the body and the signs of fatigue, after athletes performed two high intensity training sessions per day, can be assessed using the approach of the evaluation of interactions between functional variables. Therefore the evaluation of the interactions of physiological signals by using time series analysis methods is suitable for the observation of these processes and the functional state of the body.Keywords: electrocardiogram, time series, functional state.

The Contribution of Foreign Direct Investment for Economic Growth of Ethiopia: Time Series Analysis

2018 ◽  
Vol 9 (02) ◽  
Author(s):  
Addissie Melak
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Foreign Direct Investment ◽  
Time Series Analysis ◽  
Direct Investment ◽  
Policy Framework ◽  
Annual Growth Rate ◽  
African Countries ◽  
Series Analysis ◽  
Integration Test

Economic growth of countries is one of the fundamental questions in economics. Most African countries are opening their economies for welcoming of foreign investors. As such Ethiopia, like many African countries took measures to attract and improve foreign direct investment. The purpose of this study is to examine the contribution of foreign direct investment (FDI) for economic growth of Ethiopia over the period of 1981-2013. The study shows an overview of Ethiopian economy and investment environment by the help of descriptive and econometric methods of analysis to establish empirical investigation for the contribution of FDI on Ethiopian economy. OLS method of time series analysis is employed to analyse the data. The stationary of the variables have been checked by using Augmented Dickey Fuller (ADF) Unit Root test and hence they are stationery at first difference. The co- integration test also shows that there is a long run relationship between the dependent and independent variables. Accordingly, the finding of the study shows that FDI, GDP per capita, exchange rate, total investment as percentage of GDP, inflow of FDI stock, trade as percentage of GDP, annual growth rate of GDP and liberalization of the economy have positive impact on Ethiopian GDP. Whereas Gross fixed domestic investment, inflows of FDI and Gross capital formation influence economic growth of Ethiopia negatively. This finding suggests that there should be better policy framework to attract and improve the volume of FDI through creating conducive environment for investment.

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