Search results for: data correlation

Authors: Jia Zhang, Fengmei Yao, Yanjing Tan

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The accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C4 crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS-P-YEC (Remote-Sensing-Photosynthesis-Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS-P-YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002-2011. The statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (P < 0.01) between the simulated yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002-2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.

Keywords: process-based model, C4 crop, maize yield, remote sensing, Northeast China Plain

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Authors: Rajarshi Sharma, Rashidul Alam, Visavino Seleyi, Yuvila Sangtam

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The Intensity-Duration-Frequency (IDF) relationship of rainfall amounts is one of the most commonly used tools in water resources engineering for planning, design and operation of water resources project, or for various engineering projects against design floods. The establishment of such relationships was reported as early as in 1932 (Bernard). Since then many sets of relationships have been constructed for several parts of the globe. The objective of this research is to derive IDF relationship of rainfall for western watershed of Guwahati, Assam. These relationships are useful in the design of urban drainage works, e.g. storm sewers, culverts and other hydraulic structures. In the study, rainfall depth for 10 years viz. 2001 to 2010 has been collected from the Regional Meteorological Centre Borjhar, Guwahati. Firstly, the data has been used to construct the mass curve for duration of more than 7 hours rainfall to calculate the maximum intensity and to form the intensity duration curves. Gumbel’s frequency analysis technique has been used to calculate the probable maximum rainfall intensities for a period of 2 yr, 5 yr, 10 yr, 50 yr, 100 yr from the maximum intensity. Finally, regression analysis has been used to develop the intensity-duration-frequency (IDF) curve. Thus, from the analysis the values for the constants ‘a’,‘b’ &‘c’ have been found out. The values of ‘a’ for which the sum of the squared deviation is minimum has been found out to be 40 and when the corresponding value of ‘c’ and ‘b’ for the minimum squared deviation of ‘a’ are 0.744 and 1981.527 respectively. The results obtained showed that in all the cases the correlation coefficient is very high indicating the goodness of fit of the formulae to estimate IDF curves in the region of interest.

Keywords: intensity-duration-frequency relationship, mass curve, regression analysis, correlation coefficient

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Authors: Hsing Yuan Liu

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Background: Considerable theoretical and empirical work has identified a relationship between collaboration interactions and creativity in an organizational context. The mechanisms underlying this link, however, are not well understood in healthcare education. Objectives: The aims of this study were to explore the impact of collaboration interactions on team creativity and its underlying mechanism and to verify a moderated mediation model. Design, setting, and participants: This study utilized a cross-sectional, quantitative, descriptive design. The survey data were collected from 177 nursing students who enrolled in 18-week capstone courses of small interdisciplinary groups collaborating to design healthcare products in Taiwan during 2018 and 2019. Methods: Questionnaires assessed the nursing students' perceptions about their teams' swift trust (of cognition- and affect-based), conflicts (of task, process, and relationship), interaction behaviors (constructive controversy, helping behaviors, and spontaneous communication), and creativity. This study used descriptive statistics to compare demographics, swift trust scores, conflict scores, interaction behavior scores, and creativity scores for interdisciplinary teams. Data were analyzed using Pearson’s correlation coefficient and simple and hierarchical multiple regression models. Results: Pearson’s correlation analysis showed the cognition-based team swift trust was positively correlated with team creativity. The mediation model indicated constructive controversy fully mediated the effect of cognition-based team swift trust on student teams’ creativity. The moderated mediation model indicated that task conflict negatively moderates the mediating effect of the constructive controversy on the link between cognition-based team swift trust and team creativity. Conclusion: Our findings suggest nursing student teams’ interaction behaviors and task conflict are crucial mediating and moderated mediation variables on the relationship between collaboration interactions and team creativity, respectively. The empirical data confirms the validity of our proposed moderated mediation models of team creativity. Therefore, this study's validated moderated mediation model could provide guidance for nursing educators to improve collaboration interaction outcomes and creativity on nursing student teams.

Keywords: team swift trust, team conflict, team interaction behavior, moderated mediating effects, interdisciplinary education, nursing students

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

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Authors: G. S. Sumanasekara, W. M. P. B. Weerasingheg

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The major problem associated with concentrate feeds used for feeding cattle is declining quality by contamination with Aflatoxins. Objective: The aim of the study was to detect levels of Aflatoxin M1(AFM1) in cow milk , AFM1 levels present in milk related to different feed types and to identify the relationship between feed type and Aflatoxin M1 in milk. Design: cross sectional study design. Milk samples from each farm assessed for presence of AFM1 using High Performance Liquid Chromatographic method. Setting: Ten dairy farms located in Nuwara-Eliya district were randomly selected.AFM1 analysis was done using High Performance Liquid Chromatography(HPLC). Results: The results indicated that AFM1 was present in 50% of samples. Coconut poonac shown the most significant relationship among individual feeds having a correlation of 0.65 and P value of 0.042 . Among feed combinations, coconut poonac and beer pulp combination showed the highest correlation of 0.77 and P value of 0.05. Grasses had shown a very poor relationship with the AFM1 occurrence in milk (r=0.053, P=0.885). Relationship between overall concentrate feeds in the study and AFM1 in milk, it was clear that they had a significant relationship having correlation of 0.65 and P value of 0.042. Majority of samples lied between 0-10 ng L-1 of AFM1 and one sample exceeded above 30 ng L-1. Two samples had AFM1 concentrations between 22-32 ng L-1. One sample lied between 32-42ng L-1, did not exceed the EU recommended level of 50 ng L-1. The presence of AFM1 in milk under various management and feeding conditions is yet to be investigated in Sri Lanka.

Keywords: aflatoxin M1, aspergillus, cattle feed, concentrates, cow milk, high perforamance liquid chromatography

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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Authors: Vladyslav Povoroznyuk, Larysa Martynyuk, Iryna Syzonenko, Liliya Martynyuk

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Osteoporosis is one of the important problems in postmenopausal women due to an increased risk of sudden and unexpected fractures. This study is aimed to determine the connection between bone mineral density (BMD) and trabecular bone score (TBS) in Ukrainian women suffering from metabolic syndrome. Participating in the study, 566 menopausal women aged 50-79 year-old were examined and divided into two groups: Group A included 336 women with no obesity (BMI ≤ 29.9 kg/m²), and Group B – 230 women with metabolic syndrome (diagnosis according to IDF criteria, 2005). Dual-energy X-ray absorptiometry was used for measuring of lumbar spine (L1-L4), femoral neck, total body and forearm BMD and bone quality indexes (last according to Med-Imaps installation). Data were analyzed using Statistical Package 6.0. A significant increase of lumbar spine (L1-L4), femoral neck, total body and ultradistal radius BMD was found in women with metabolic syndrome compared to those without obesity (p < 0.001) both in their totality and in groups of 50-59 years, 60-69 years, and 70-79 years. TBS was significantly higher in non-obese women compared to metabolic syndrome patients of 50-59 years and in the general sample (p < 0.05). Analysis showed significant positive correlation between body mass index (BMI) and BMD at all levels. Significant negative correlation between BMI and TBS (L1-L4) was established. Despite the fact that BMD indexes were significantly higher in women with metabolic syndrome, the frequency of vertebral and non-vertebral fractures did not differ significantly in the groups of patients.

Keywords: bone mineral density, trabecular bone score, metabolic syndrome, fracture

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Authors: Enes Ergün, Sedat Geli̇bolu

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The purpose of this study is to determine the relationship between self-efficacy and subjective well-being among university students. We are aiming to determine whether self efficacy of university students predicts their subjective well-being and if there is a statistically significant difference among boys and girls in this context. Sample of this study consists of 245 university students from Çanakkale, ages ranging between 17 and 24. 72% (n=171) of the participants were girls and 28% (n=69) boys. Three different scales were utilized as data collection tools that Life Satisfaction Scale, General Self-Efficacy Scale, and Positive Negative Experiences Scale. Pearson correlation coefficient, independent sample t test and simple linear regression were used for data analyses. Results showed that well-being is significantly correlated with self-efficacy and self-efficacy is a statistically significant predictor of well-being too. In terms of gender differences, there is no significant difference between self-efficacy scores of boys and girls which shows the same case with well being scores, as well. Fostering university students' academic, social and emotional self-efficacy will increase their well-being which is very important for young adults especially their freshman years.

Keywords: positive psychology, self-efficacy, subjective well being, university students

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Authors: Talib M. Albayati, Omar S. Mahdy, Ghanim M. Alwan

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This work is aimed to prepare magnetic nanoporous material Fe/MCM-41 and study its Physical characterization in order to enhance the magnetic properties for study the operating conditions on separation efficiency of methyl orange (MO) from wastewater by adsorption process. The experimental results are analysed to select the best operating conditions for different studied parameters which were obtained for both adsorbents mesoporous material samples MCM-41 and magnetic Fe/MCM-41 as follow: constant temperature (20 ºC), pH: (2) adsorbent dosage (0.03 gm), contact time (10 minute) and concentrations (30 mg/L). The results are demonstrated that the adsorption processes can be well fitted by the Langmuir isotherm model for pure MCM-41 with a higher correlation coefficient (0.999) and fitted by the freundlich isotherm model for magnetic Fe/MCM-41 with a higher correlation coefficient of (0.994).

Keywords: adsorption, nanoporous materials, mcm-41, magnetic material, wastewater, orange, wastewater

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Authors: Somnath Mukhuti, Prem Kumar Ghosh

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Background and significance of the study Indian stock market has undergone sudden changes after the current China crisis in terms of turnover, market capitalization, share prices, etc. The average returns on equity investment in both markets have more than three and half times after global financial crisis owing to the development of industrial activity, corporate sectors development, enhancement in global consumption, change of global financial association and fewer imports from developed countries. But the economic policies of both the economies are far different, that is to say, where Indian economy maintaining a conservative policy, Chinese economy maintaining an aggressive policy. Besides this, Chinese economy recently lowering its currency for increasing mysterious growth but Indian does not. But on August 24, 2015 Indian stock market and world stock markets were fall down due to the reason of Chinese stock market. Keeping in view of the above, this study seeks to examine the influence of Chinese stock on Indian stock market. Methodology This research work is based on daily time series data obtained from yahoo finance database between 2009 (April 1) to 2015 (September 28). This study is based on two important stock markets, that is, Indian stock market (Bombay Stock Exchange) and Chinese stock market (Shanghai Stock Exchange). In the course of analysis, the daily raw data were converted into natural logarithm for minimizing the problem of heteroskedasticity. While tackling the issue, correlation statistics, ADF and PP unit root test, bivariate cointegration test and causality test were used. Major findings Correlation statistics show that both stock markets are associated positively. Both ADF and PP unit root test results demonstrate that the time series data were not normal and were not stationary at level however stationary at 1st difference. The bivariate cointegration test results indicate that the Indian stock market was associated with Chinese stock market in the long-run. The Granger causality test illustrates there was a unidirectional causality between Indian stock market and Chinese stock market. Concluding statement The empirical results recommend that India’s stock market was not very much dependent on Chinese stock market because of Indian economic conservative policies. Nevertheless, Indian stock market might be sturdy if Indian economic policies are changed slightly and if increases the portfolio investment with Chinese economy. Indian economy might be a third largest economy in 2030 if India increases its portfolio investment and trade relations with both Chinese economy and US economy.

Keywords: Indian stock market, China stock market, bivariate cointegration, causality test

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Authors: Bisola Olumegbon

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Globally, there were about 229 million cases of malaria in 2022. The sub-Saharan African region accounted for 92% of the reported cases and 94% of deaths. Nigeria had the highest number of malaria cases and deaths, representing 27% of global cases. This scholarly project was a case study guided by the political determinants of health. Triangulation of data using thematic analysis was used to identify the political determinants of malaria in Nigeria and to understand how the concept of interaction contributes to the persistence of the disease. The analysis involved a deductive and inductive approach based on the literature review and the evidence of political determinants gathered in the data. Participants’ in-depth interviews were used to collect data from frontline personnel. Data triangulation was done using thematic analysis, a method used to identify patterns and themes in qualitative data. The study findings revealed a correlation between political determinants of health and malaria management efforts in Nigeria. Some influencing factors included voting challenges, inadequate funding, lack of health priority from the government, noncompliance among patients, and hurdles to effective communication. The findings suggest a need to deliberately increase dedication to the political agenda, provide sufficient financial resources, enhance communication, and active community involvement to address the persistent malaria endemic effectively. Further study is recommended to identify interventions to address identified factors of political determinants of health to reduce malaria in Nigeria. Such intervention must involve collaboration with diverse stakeholders such as policymakers, healthcare professionals, community leaders, and researchers.

Keywords: malaria, malaria management, health worker, stakeholders, political determinant of health

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Authors: Maria Sciammarella, Uttam M. Shrestha, Youngho Seo, Grant T. Gullberg, Elias H. Botvinick

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Background: Myocardial perfusion imaging (MPI) is typically performed with static imaging protocols and visually assessed for perfusion defects based on the relative intensity distribution. Dynamic cardiac SPECT, on the other hand, is a new imaging technique that is based on time varying information of radiotracer distribution, which permits quantification of myocardial blood flow (MBF). In this abstract, we report a progress and current status of dynamic cardiac SPECT using conventional gamma camera (Infinia Hawkeye 4, GE Healthcare) for estimation of myocardial blood flow and coronary flow reserve. Methods: A group of patients who had high risk of coronary artery disease was enrolled to evaluate our methodology. A low-dose/high-dose rest/pharmacologic-induced-stress protocol was implemented. A standard rest and a standard stress radionuclide dose of ⁹⁹ᵐTc-tetrofosmin (140 keV) was administered. The dynamic SPECT data for each patient were reconstructed using the standard 4-dimensional maximum likelihood expectation maximization (ML-EM) algorithm. Acquired data were used to estimate the myocardial blood flow (MBF). The correspondence between flow values in the main coronary vasculature with myocardial segments defined by the standardized myocardial segmentation and nomenclature were derived. The coronary flow reserve, CFR, was defined as the ratio of stress to rest MBF values. CFR values estimated with SPECT were also validated with dynamic PET. Results: The range of territorial MBF in LAD, RCA, and LCX was 0.44 ml/min/g to 3.81 ml/min/g. The MBF between estimated with PET and SPECT in the group of independent cohort of 7 patients showed statistically significant correlation, r = 0.71 (p < 0.001). But the corresponding CFR correlation was moderate r = 0.39 yet statistically significant (p = 0.037). The mean stress MBF value was significantly lower for angiographically abnormal than that for the normal (Normal Mean MBF = 2.49 ± 0.61, Abnormal Mean MBF = 1.43 ± 0. 0.62, P < .001). Conclusions: The visually assessed image findings in clinical SPECT are subjective, and may not reflect direct physiologic measures of coronary lesion. The MBF and CFR measured with dynamic SPECT are fully objective and available only with the data generated from the dynamic SPECT method. A quantitative approach such as measuring CFR using dynamic SPECT imaging is a better mode of diagnosing CAD than visual assessment of stress and rest images from static SPECT images Coronary Flow Reserve.

Keywords: dynamic SPECT, clinical SPECT/CT, selective coronary angiograph, ⁹⁹ᵐTc-Tetrofosmin

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Authors: Zahraa Albasry, Hadeel D. Najim, Anmar Al-Taie

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Background: Hypertension is considered as one of the most important causes of cardiovascular complications and one of the leading causes of worldwide mortality. Identifying the potential risk factors associated with this medical health problem plays an important role in minimizing its incidence and related complications. The objective of this study is to explore the prevalence of receptor sensitivity regarding assess and understand the perception of specific predictive confounding factors on the prevalence of hypertension (HT) among a sample of Iraqi population in Baghdad, Iraq. Materials and Methods: A randomized cross sectional study was carried out on 100 adult subjects during their visit to the outpatient clinic at a certain sector of Baghdad Province, Iraq. Demographic, clinical and health records alongside specific screening and laboratory tests of the participants were collected and analyzed to detect the potential of confounding factors on the prevalence of HT. Results: 63% of the study participants suffered from HT, most of them were female patients (P < 0.005). Patients aged between 41-50 years old significantly suffered from HT than other age groups (63.5%, P < 0.001). 88.9% of the participants were obese (P < 0.001) and 47.6% had diabetes with HT. Positive family history and sedentary lifestyle were significantly higher among all hypertensive groups (P < 0.05). High salt and fatty food intake was significantly found among patients suffered from isolated systolic hypertension (ISHT) (P < 0.05). A significant positive correlation between packed cell volume (PCV) and systolic blood pressure (SBP) (r = 0.353, P = 0.048) found among normotensive participants. Among hypertensive patients, a positive significant correlation found between triglycerides (TG) and both SBP (r = 0.484, P = 0.031) and diastolic blood pressure (DBP) (r = 0.463, P = 0.040), while low density lipoprotein-cholesterol (LDL-c) showed a positive significant correlation with DBP (r = 0.443, P = 0.021). Conclusion: The prevalence of HT among Iraqi populations is of major concern. Further consideration is required to detect the impact of potential risk factors and to minimize blood pressure (BP) elevation and reduce the risk of other cardiovascular complications later in life.

Keywords: Correlation, Hypertension, Iraq, Risk factors

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Authors: Arturo Daag

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The Philippine Institute of Volcanology and Seismology (PHIVOLCS) is enhancing its liquefaction hazard map towards a detailed probabilistic approach using SDS and geophysical data. Target sites for liquefaction assessment are public schools in Metro Manila. Since target sites are in highly urbanized-setting, the objective of the project is to conduct both non-destructive geotechnical studies using Screw Driving Testing (SDFS) combined with geophysical data such as refraction microtremor array (ReMi), 3 component microtremor Horizontal to Vertical Spectral Ratio (HVSR), and ground penetrating RADAR (GPR). Initial test data was conducted in liquefaction impacted areas from the Mw 6.1 earthquake in Central Luzon last April 22, 2019 Province of Pampanga. Numerous accounts of liquefaction events were documented areas underlain by quaternary alluvium and mostly covered by recent lahar deposits. SDS estimated values showed a good correlation to actual SPT values obtained from available borehole data. Thus, confirming that SDS can be an alternative tool for liquefaction assessment and more efficient in terms of cost and time compared to SPT and CPT. Conducting borehole may limit its access in highly urbanized areas. In order to extend or extrapolate the SPT borehole data, non-destructive geophysical equipment was used. A 3-component microtremor obtains a subsurface velocity model in 1-D seismic shear wave velocity of the upper 30 meters of the profile (Vs30). For the ReMi, 12 geophone array with 6 to 8-meter spacing surveys were conducted. Microtremor data were computed through the Factor of Safety, which is the quotient of Cyclic Resistance Ratio (CRR) and Cyclic Stress Ratio (CSR). Complementary GPR was used to study the subsurface structure and used to inferred subsurface structures and groundwater conditions.

Keywords: screw drive testing, microtremor, ground penetrating RADAR, liquefaction

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Authors: Razaq A. Olaitan, Ayansina Ayanlade

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Understanding aerosol properties is the main goal of global research in order to lower the uncertainty associated with climate change in the trends and magnitude of aerosol particles. In order to identify aerosol particle types, optical properties, and the relationship between aerosol properties and particle concentration between 2019 and 2021, a study conducted in Ilorin, Nigeria, examined the aerosol robotic network's ground-based sun/sky scanning radiometer. The AERONET algorithm version 2 was utilized to retrieve monthly data on aerosol optical depth and angstrom exponent. The version 3 algorithm, which is an almucantar level 2 inversion, was employed to retrieve daily data on single scattering albedo and aerosol size distribution. Excel 2016 was used to analyze the data's monthly, seasonal, and annual mean averages. The distribution of different types of aerosols was analyzed using scatterplots, and the optical properties of the aerosol were investigated using pertinent mathematical theorems. To comprehend the relationships between particle concentration and properties, correlation statistics were employed. Based on the premise that aerosol characteristics must remain constant in both magnitude and trend across time and space, the study's findings indicate that the types of aerosols identified between 2019 and 2021 are as follows: 29.22% urban industrial (UI) aerosol type, 37.08% desert (D) aerosol type, 10.67% biomass burning (BB), and 23.03% urban mix (Um) aerosol type. Convective wind systems, which frequently carry particles as they blow over long distances in the atmosphere, have been responsible for the peak-of-the-columnar aerosol loadings, which were observed during August of the study period. The study has shown that while coarse mode particles dominate, fine particles are increasing in seasonal and annual trends. Burning biomass and human activities in the city are linked to these trends. The study found that the majority of particles are highly absorbing black carbon, with the fine mode having a volume median radius of 0.08 to 0.12 meters. The investigation also revealed that there is a positive coefficient of correlation (r = 0.57) between changes in aerosol particle concentration and changes in aerosol properties. Human activity is rapidly increasing in Ilorin, causing changes in aerosol properties, indicating potential health risks from climate change and human influence on geological and environmental systems.

Keywords: aerosol loading, aerosol types, health risks, optical properties

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Authors: Abdelmounaim Lahrech, Hajar Bousfiha

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This paper examines equity market integration between Morocco and France and its consequent implications on international portfolio diversification. In the absence of stock market linkages, Morocco can act as a diversification destination to European investors, allowing higher returns at a comparable level of risk in developed markets. In contrast, this attractiveness is limited if both financial markets show significant linkage. The research empirically measures financial market’s integration in by capturing the conditional correlation between the two markets using the Generalized Autoregressive Conditionally Heteroscedastic (GARCH) model. Then, the research uses the Dynamic Conditional Correlation (DCC) model of Engle (2002) to track the correlations. The research findings show that there is no important increase over the years in the correlation between the Moroccan and the French equity markets, even though France is considered Morocco’s first trading partner. Failing to prove evidence of the stock index linkage between the two countries, the volatility series of each market were assumed to change over time separately. Yet, the study reveals that despite the important historical and economic linkages between Morocco and France, there is no evidence that equity markets follow. The small correlations and their stationarity over time show that over the 10 years studied, correlations were fluctuating around a stable mean with no significant change at their level. Different explanations can be attributed to the absence of market linkage between the two equity markets.

Keywords: equity market linkage, DCC GARCH, international portfolio diversification, Morocco, France

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Authors: Annapureddy Srikant Reddy, Atthanti Mahendra, Samala Chinni Krishna, N. Neelima

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In our present world, we are generating a lot of data and we, need a specific device to store all these data. Generally, we store data in pen drives, hard drives, etc. Sometimes we may loss the data due to the corruption of devices. To overcome all these issues, we implemented a cloud space for storing the data, and it provides more security to the data. We can access the data with just using the internet from anywhere in the world. We implemented all these with the java using Net beans IDE. Once user uploads the data, he does not have any rights to change the data. Users uploaded files are stored in the cloud with the file name as system time and the directory will be created with some random words. Cloud accepts the data only if the size of the file is less than 2MB.

Keywords: cloud space, AES, FTP, NetBeans IDE

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Authors: Jeyaseelan Maria Michael

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This study investigated the prevalence of cyberbullying among college female students and its effects on their psychological well-being. The respondents were from the age group of 17 and 18, doing the first-year college in Tamilnadu, India. In this study, 110 participants were selected through simple random sampling. The standardized questionnaire of David Alvare-Garcia’s Cybervictimization Questionnaire for Adolescents (CYVIC) and Ryff’s Psychological Well-Being (PWB) were administered for data collection. CYVIC has four subdomains namely, impersonation, visual-sexual cybervictimization, written-verbal cybervictimization, online exclusion. Ryff’s PWB has six domains namely, autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self- acceptance. The collected data were analyzed by SPSS v.23. The results indicate that cyberbullying prevails among college female students (M=1.24, SD= .21). Among the participants, 17 are scored one standard deviation above the mean (1.45). Among the subdomains of the CYVIC, the respondents have the highest score (M=1.40, SD= .38) in written-verbal cybervictimization. Cyber victimization has a significant correlation at the 0.01 level with psychological well-being.

Keywords: college students, cyberbullying, cyber victimization, psychological well-being

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Authors: Ivana Knezevic, Kenneth D. Candido, N. Nick Knezevic

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Background: While pain intensity scales remain generally accepted assessment tool, and the numeric pain rating score is highly subjective, we nevertheless rely on them to make a judgment about treatment effects. Misinterpretation of pain can lead practitioners to underestimate or overestimate the patient’s medical condition. The purpose of this study was to analyze how the numeric rating pain scores given by patients with low back pain correlate with their functional activity levels. Methods: We included 100 consecutive patients with radicular low back pain (LBP) after the Institutional Review Board (IRB) approval. Pain scores, numeric rating scale (NRS) responses at rest and in the movement,Oswestry Disability Index (ODI) questionnaire answers were collected 10 times through 12 months. The ODI questionnaire is targeting a patient’s activities and physical limitations as well as a patient’s ability to manage stationary everyday duties. Statistical analysis was performed by using SPSS Software version 20. Results: The average duration of LBP was 14±22 months at the beginning of the study. All patients included in the study were between 24 and 78 years old (average 48.85±14); 56% women and 44% men. Differences between ODI and pain scores in the range from -10% to +10% were considered “normal”. Discrepancies in pain scores were graded as mild between -30% and -11% or +11% and +30%; moderate between -50% and -31% and +31% and +50% and severe if differences were more than -50% or +50%. Our data showed that pain scores at rest correlate well with ODI in 65% of patients. In 30% of patients mild discrepancies were present (negative in 21% and positive in 9%), 4% of patients had moderate and 1% severe discrepancies. “Negative discrepancy” means that patients graded their pain scores much higher than their functional ability, and most likely exaggerated their pain. “Positive discrepancy” means that patients graded their pain scores much lower than their functional ability, and most likely underrated their pain. Comparisons between ODI and pain scores during movement showed normal correlation in only 39% of patients. Mild discrepancies were present in 42% (negative in 39% and positive in 3%); moderate in 14% (all negative), and severe in 5% (all negative) of patients. A 58% unknowingly exaggerated their pain during movement. Inconsistencies were equal in male and female patients (p=0.606 and p=0.928).Our results showed that there was a negative correlation between patients’ satisfaction and the degree of reporting pain inconsistency. Furthermore, patients talking opioids showed more discrepancies in reporting pain intensity scores than did patients taking non-opioid analgesics or not taking medications for LBP (p=0.038). There was a highly statistically significant correlation between morphine equivalents doses and the level of discrepancy (p<0.0001). Conclusion: We have put emphasis on the patient education in pain evaluation as a vital step in accurate pain level reporting. We have showed a direct correlation with patients’ satisfaction. Furthermore, we must identify other parameters in defining our patients’ chronic pain conditions, such as functionality scales, quality of life questionnaires, etc., and should move away from an overly simplistic subjective rating scale.

Keywords: pain score, functionality scales, low back pain, lumbar

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Authors: Moti Zwilling, Srečko Natek

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This paper aims to present an innovative predictive analytics analysis in order to find the best combination between two consumers who strive to find their partner or in internet sites. The methodology shown in this paper is based on analysis of consumer preferences and involves data mining and machine learning search techniques. The study is composed of two parts: The first part examines by means of descriptive statistics the correlations between a set of parameters that are taken between man and women where they intent to meet each other through the social media, usually the internet. In this part several hypotheses were examined and statistical analysis were taken place. Results show that there is a strong correlation between the affiliated attributes of man and woman as long as concerned to how they present themselves in a social media such as "Facebook". One interesting issue is the strong desire to develop a serious relationship between most of the respondents. In the second part, the authors used common data mining algorithms to search and classify the most important and effective attributes that affect the response rate of the other side. Results exhibit that personal presentation and education background are found as most affective to achieve a positive attitude to one's profile from the other mate.

Keywords: dating sites, social networks, machine learning, decision trees, data mining

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Authors: Sintija Miļuna, Ričards Melderis, Loreta Briuka, Dagnija Rostoka, Ingus Skadiņš, Juta Kroiča

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Objectives Smokeless tobacco products in Latvia become more available and favorable to young adults, especially students and athletes like hockey and floorball players. The aim of the research was to detect visual mucosal changes in the oral cavity in smokeless tobacco users and to evaluate pro - inflammatory and anti - inflammatory cytokine (IL-6, IL-1, IL-8, TNF Alpha) levels in saliva from smokeless tobacco users. Methods A smokeless tobacco group (n=10) and a control group (non-tobacco users) (n=10) were intraorally examined for oral lesions and 5 ml of saliva were collected. Saliva was analysed for Il-6, IL-1, Il-8, TNF Alpha using ELISA Sigma-Aldrich. For statistical analysis IBM Statistics 27 was used (Mann - Whitney U test, Spearman’s Rank Correlation coefficient). This research was approved by the Ethics Committee of Rīga Stradiņš University No.22/28.01.2016. This research has been developed with financing from the European Social Fund and Latvian state budget within the project no. 8.2.2.0/20/I/004 “Support for involving doctoral students in scientific research and studies” at Rīga Stradiņš University. Results IL-1, IL-6, IL-8, TNF Alpha levels were higher in the smokeless tobacco group (IL-1 83.34 pg/ml vs. 74.26 pg/ml; IL-6 195.10 pg/ml vs. 6.16 pg/ml; IL-8 736.34 pg/ml vs. 285.26 pg/ml; TNF Alpha 489.27 pg/ml vs. 200.9 pg/ml), but statistically there is no difference between control group and smokeless tobacco group (IL1 p=0.190, IL6 p=0.052, IL8 p=0.165, TNF alpha p=0.089). There was statistical correlation between IL1 and IL6 (p=0.023), IL6 and TNF alpha (p=0.028), IL8 and IL6 (p=0.005). Conclusions White localized lesions were detected in places where smokeless tobacco users placed sachets. There is a statistical correlation between IL6 and IL1 levels, IL6 and TNF alpha levels, IL8 and IL6 levels in saliva. There are no differences in the inflammatory cytokine levels between control group and smokeless tobacco group.

Keywords: smokeless tobacco, Snus, inflammatory biomarkers, oral lesions, oral pathology

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Authors: Marwa Mamdouh Shaban, Nagat Saied Habib, Shireen Ezz El-Din Taha, Eman Mahmoud Seif El-Naser

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Background: Dental nurses and dentists were constantly exposed to a number of specific work related health risk factors which develop and intensify with years. Awareness regarding these work-related health risk factors and implementation of preventive health care measures could provide a safe work environment for all dental nurses and dentists. Aim of the study: to assess the work-related health risk factors among dental nurses and dentists and preventive health care measures applied among dental nurses and dentists. Research design: A descriptive design was utilized. Sample: Convenience sample of 50 dental nurses and 150 dentists were included in the current study. Setting: This study was conducted at the dental clinics at faculty of oral and dental medicine, Al-Kasr Al Ainy Hospital. Tools of data collection: Three tools were developed, tested for clarity, and feasibility: a-Socio-demographic data sheet, b-Work-related health risk factors questionnaire, and c-structured observational checklist. Results: The most common work risk factors prevailing among dental nurses were emotional exhaustion (82%), low back pain (76%) and latex allergy (62%) and the most common work risk factors prevailing among dentists were percutaneous exposure incident (100%), emotional exhaustion (100%) and low back pain (93.3%). Also, statistically significant negative correlation (r=-0.274, at p = 0.045) between the incidence of chemical health risk factors and application of chemical preventive measures among dental nurses. A statistically significant negative correlation (r=-0.177, at p = 0.030) between the incidences of mechanical health risk factors among dentists and application of mechanical preventive measures. Conclusion: The studied dental nurses and dentists exposed to many work related health risk factors as latex allergy, percutaneous exposure incidents, low back pain and emotional exhaustion related to inappropriate application of preventive health care measures. Recommendation: Raise awareness of dental nurses and dentists about work-related health risk factors, design and implement health education program for preventive health care measures.

Keywords: work-related risk factors, preventive measures, nurses, dentists

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Authors: Luh Eka Suryani, Purhadi

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Poisson regression is a non-linear regression model with response variable in the form of count data that follows Poisson distribution. Modeling for a pair of count data that show high correlation can be analyzed by Poisson Bivariate Regression. Data, the number of infant mortality and maternal mortality, are count data that can be analyzed by Poisson Bivariate Regression. The Poisson regression assumption is an equidispersion where the mean and variance values are equal. However, the actual count data has a variance value which can be greater or less than the mean value (overdispersion and underdispersion). Violations of this assumption can be overcome by applying Generalized Poisson Regression. Characteristics of each regency can affect the number of cases occurred. This issue can be overcome by spatial analysis called geographically weighted regression. This study analyzes the number of infant mortality and maternal mortality based on conditions in East Java in 2016 using Geographically Weighted Bivariate Generalized Poisson Regression (GWBGPR) method. Modeling is done with adaptive bisquare Kernel weighting which produces 3 regency groups based on infant mortality rate and 5 regency groups based on maternal mortality rate. Variables that significantly influence the number of infant and maternal mortality are the percentages of pregnant women visit health workers at least 4 times during pregnancy, pregnant women get Fe3 tablets, obstetric complication handled, clean household and healthy behavior, and married women with the first marriage age under 18 years.

Keywords: adaptive bisquare kernel, GWBGPR, infant mortality, maternal mortality, overdispersion

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Authors: Rios A. S., Hild F., Deus E. P., Aimedieu P., Benallal A.

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The damage micromechanisms of chopped strand mats manufactured by compression of Brazilian coconut fiber and coconut fibers in different external conditions (chemical treatment) were used in this study. Mechanical analysis testing uniaxial traction were used with Digital Image Correlation (DIC). The images captured during the tensile test in the coconut fibers and coconut fiber mats showed an uncertainty of measurement in order centipixels. The initial modulus (modulus of elasticity) and tensile strength decreased with increasing diameter for the four conditions of coconut fibers. The DIC showed heterogeneous deformation fields for coconut fibers and mats and the displacement fields showed the rupture process of coconut fiber. The determination of poisson’s ratio of the mat was performed through of transverse and longitudinal deformations found in the elastic region.

Keywords: coconut fiber, mechanical behavior, digital image correlation, micromechanism

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Authors: Milica Lazic, Jovana Jestrovic

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The aim of this research is to examine moderating role of positive and negative affect, defined as traits, in relationship between a number of stressful life events to which an individual is exposed and life satisfaction. The tendency to experience positive and negative emotions is considered as relatively independent, and life satisfaction depends on presence and intensity of emotions of different valence. However, the role of positive and negative affect can be much more complex. It can change the direction and/or intensity of correlation between a number of stressful life events and life satisfaction. Thus, this question is important for two reasons, (I) better comprehension of inconsistent result of correlation intensity between stressful events and life satisfaction (II) verification on what conditions positive and negative affect have a protective role, and on what conditions the positive and/or negative affect is vulnerability factor. Longitudinal data were collected in two waves from 660 adolescents. Firstly, participants completed the Positive and Negative Affect Schedule. A year later, Life events questionnaire, which measures the number of stressful events in the past six months and Satisfaction with Life Scale were administered. The data were analyzed using hierarchical regression analyses: three-way interaction. The results show that number of life events, positive and negative effect contribute to the level of life satisfaction. The check of moderation role shows the significant three-way interaction of number of life event, and both, positive and negative affect. Individuals who report high level of positive affect, estimate to be moderate to highly satisfied with their lives, regardless of number of stressors to which they are exposed and also how often they experience negative emotions. Individuals, who often experience negative emotions and rarely positive, report the lowest level of life satisfaction. It doesn't change despite the number of stressors they were exposed to. Individuals who report that rarely experience not only positive than also negative emotions estimate different level of life satisfaction depending on number of stressors they were exposed to. Under the influence of numerous stressors, their level of life satisfaction is low, and it's equal to life satisfaction level of individuals who often experience negative and rarely positive emotions. The result of this research shows that tendency to often experience positive emotions is the protective factor in situation when individuals are exposed to high number of stressors. On the other hand, tendency to rarely experience positive emotions present vulnerability factor. Conclusions and practical implications are further discussed.

Keywords: life events, life satisfaction, subjective well-being, positive and negative affect

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Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

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Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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Authors: S. Channgam, A. Sae-Tang, T. Termsaithong

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In this research, the occurrences of large size events in various system sizes of the Bak-Tang-Wiesenfeld sandpile model are considered. The system sizes (square lattice) of model considered here are 25×25, 50×50, 75×75 and 100×100. The cross-correlation between the ratio of sites containing 3 grain time series and the large size event time series for these 4 system sizes are also analyzed. Moreover, a prediction method of the large-size event for the 50×50 system size is also introduced. Lastly, it can be shown that this prediction method provides a slightly higher efficiency than random predictions.

Keywords: Bak-Tang-Wiesenfeld sandpile model, cross-correlation, avalanches, prediction method

Procedia PDF Downloads 380

Authors: Shalini Rankawat, Mansi Rankawat, Rahul Dubey, Mazad Zaveri

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Physiological signals such as electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often seriously corrupted by noise, artifacts, and missing data, which lead to errors in the estimation of heart rate (HR) and incidences of false alarm from ICU monitors. Clinical support in ICU requires most reliable heart rate estimation. Cardiac activity, because of its relatively high electrical energy, may introduce artifacts in Electroencephalogram (EEG), Electrooculogram (EOG), and Electromyogram (EMG) recordings. This paper presents a robust heart rate estimation method by detection of R-peaks of ECG artifacts in EEG, EMG & EOG signals, using energy-based function and a novel Signal Quality Index (SQI) assessment technique. SQIs of physiological signals (EEG, EMG, & EOG) were obtained by correlation of nonlinear energy operator (teager energy) of these signals with either ECG or ABP signal. HR is estimated from ECG, ABP, EEG, EMG, and EOG signals from separate Kalman filter based upon individual SQIs. Data fusion of each HR estimate was then performed by weighing each estimate by the Kalman filters’ SQI modified innovations. The fused signal HR estimate is more accurate and robust than any of the individual HR estimate. This method was evaluated on MIMIC II data base of PhysioNet from bedside monitors of ICU patients. The method provides an accurate HR estimate even in the presence of noise and artifacts.

Keywords: ECG, ABP, EEG, EMG, EOG, ECG artifacts, Teager-Kaiser energy, heart rate, signal quality index, Kalman filter, data fusion

Procedia PDF Downloads 693

Authors: Saima Kalsoom, Sobia Masood, Muhammad Faran

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This study aimed to examine the association between emotional intelligence and gender role attitudes of married individuals. Another aim of this study was to test the moderating role of gender work status of married individuals for predicting gender role attitudes from emotional intelligence. A sample of (N = 500) married working men and women (both working & housewives) was approached through purposive convenience sampling technique. The data was collected employing cross-sectional research design. The indigenous versions of the Gender Role Attitudes Scale and perceived Emotional Intelligence Scale were used. The results of alpha coefficients for both the scales and subscales used in this study designated satisfactory evidence for internal consistency and reliability. Assessment of correlation coefficients showed significant positive correlation between gender role attitudes and emotional intelligence, subfactors of emotional intelligence i.e., emotional self-regulation, emotional self-awareness, and interpersonal skills with gender role attitudes. Results of model testing revealed that gender (the effect was significant for women) and work status (the effect was more significant for married working women than married working men and housewives) of the married individuals significantly moderated the relationship between emotional intelligence and gender role attitudes into the positive direction. Further, it was also found that gender and work status also moderated the relationship between emotional self-regulation (as sub factor of emotional intelligence) and gender role attitudes in a positive direction. In conclusion, this empirical evidence is vital contribution derived from the traditional and collectivistic socio-cultural background of Pakistan.

Keywords: gender role attitudes, emotional intelligence, emotional self-regulation, gender, work status, married working women

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Authors: Linara Salikhova, Elmira Nizamova, Aleksandra Katasonova, Gleb Vitkov, Olga Sarapulova.

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While most European cities conduct research on heat-related risks, there is a research gap in the Caucasus region, particularly in Yerevan, Armenia. This study aims to test the method of establishing a correlation between urban heat islands (UHI) and urban greenery distribution for prioritization of heat-vulnerable areas for revegetation. Armenia has failed to consider measures to mitigate UHI in urban development strategies despite a 2.1°C increase in average annual temperature over the past 32 years. However, planting vegetation in the city is commonly used to deal with air pollution and can be effective in reducing UHI if it prioritizes heat-vulnerable areas. The research focuses on establishing such priorities while considering the distribution of urban greenery across the city. The lack of spatially explicit air temperature data necessitated the use of satellite images to achieve the following objectives: (1) identification of land surface temperatures (LST) and quantification of temperature variations across districts; (2) classification of massifs of land surface types using normalized difference vegetation index (NDVI); (3) correlation of land surface classes with LST. Examination of the heat-vulnerable city areas (in this study, the proportion of individuals aged 75 years and above) is based on demographic data (Census 2011). Based on satellite images (Sentinel-2) captured on June 5, 2021, NDVI calculations were conducted. The massifs of the land surface were divided into five surface classes. Due to capacity limitations, the average LST for each district was identified using one satellite image from Landsat-8 on August 15, 2021. In this research, local relief is not considered, as the study mainly focuses on the interconnection between temperatures and green massifs. The average temperature in the city is 3.8°C higher than in the surrounding non-urban areas. The temperature excess ranges from a low in Norq Marash to a high in Nubarashen. Norq Marash and Avan have the highest tree and grass coverage proportions, with 56.2% and 54.5%, respectively. In other districts, the balance of wastelands and buildings is three times higher than the grass and trees, ranging from 49.8% in Quanaqer-Zeytun to 76.6% in Nubarashen. Studies have shown that decreased tree and grass coverage within a district correlates with a higher temperature increase. The temperature excess is highest in Erebuni, Ajapnyak, and Nubarashen districts. These districts have less than 25% of their area covered with grass and trees. On the other hand, Avan and Norq Marash districts have a lower temperature difference, as more than 50% of their areas are covered with trees and grass. According to the findings, a significant proportion of the elderly population (35%) aged 75 years and above reside in the Erebuni, Ajapnyak, and Shengavit neighborhoods, which are more susceptible to heat stress with an LST higher than in other city districts. The findings suggest that the method of comparing the distribution of green massifs and LST can contribute to the prioritization of heat-vulnerable city areas for revegetation. The method can become a rationale for the formation of an urban greening program.

Keywords: heat-vulnerability, land surface temperature, urban greenery, urban heat island, vegetation

Procedia PDF Downloads 70