scholarly journals Evaluating the components of social and economic resilience: After two large earthquake disasters Rudbar 1990 and Bam 2003

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Amir Bastaminia ◽  
Mohammad R. Rezaei ◽  
Mohammad H. Saraei
Keyword(s):  
Neural Network ◽  
Social Capital ◽  
Linear Regression ◽  
Length Of Stay ◽  
Household Income ◽  
Household Head ◽  
Large Earthquake ◽  
Economic Resilience ◽  
Management Plans ◽  
Different Dimensions

Extensive damages of natural disasters have made resilience a focus of disaster management plans in order to limit damages. The aim of this study was a comparative evaluation of social and economic resilience in Bam and Rudbar. This applied research attempted to quantify and compare different dimensions of social and economic resilience in Bam and Rudbar with a descriptive-analytical method. Cochran’s formula determined the sample size as 330 households from both cities (a total of 660 households). The indicators of social and economic resilience were identified from the literature, and then data were collected through a field study using questionnaires. Data were analysed using multiple linear regression and feedforward multilayer perceptron artificial neural network. Results denoted that several resilientrelated socio-economic features were significantly different for Bam and Rudbar cities, such as the number of earthquakes experienced, length of stay in current neighbourhood and mean individual and household income. Mean social and economic resilience scores were significantly higher for Rudbar (216.3 ± 33.4 and 30.6 ± 7.3) compared to Bam (193 ± 26.5 and 29.4 ± 7.07) ( p < 0.05). In addition, linear regression indicated that an increase in education level of the household head, length of stay in current neighbourhood and household income could result in an increase in social and economic resilience of the households under study. Neural network analysis revealed that social capital and employment recovery are the most and least effective factors, respectively, in both cities. In the population under study, social component, namely, social capital, was the most important determinant of resilience.

scholarly journals Determinants of Household Income Incase of Dera District, Oromia Regional State, Ethiopia

2021 ◽  
Author(s):  
Dereje Gebeyehu Ababu ◽  
Tadesse Ayele Belachew ◽  
Abate Tadesse Zeleke
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Household Income ◽  
Household Head ◽  
Multiple Linear Regression Model ◽  
Least Square ◽  
Farm Size ◽  
Primary Data ◽  
Secondary Source ◽  
Regional State

Background: Agriculture plays a key role in economic growth, as a source of raw materials, means of income generation, food security, poverty alleviation and employment to the rural population in both developed and developing countries. This study was aimed to investigate the determinants of household income incase of Dera district, Oromia Regional State, Ethiopia. Methods: The study was conducted in Dera district from September 2020 to May 2021 at Salale University, Ethiopia. Both primary and secondary source of data were used to obtain the data. Primary data was collected from the selected sample of 234 household heads using structured questionnaire. Multistage random sampling technique was used to select representative sample from Dera district. Both Descriptive statistics (frequency, percentage, mean, variance, etc.) and Econometrics model (multiple linear regression model) were used to achieve the objectives of the study and to analysis the data. Result: Using multiple linear regression of two stage least square, household income was significantly affected by place of residence, women household head, women year of education, farm size, access to credit, tropical livestock Unit and women time use at 5% significance level.

scholarly journals La integración social de las “segundas generaciones” de africanos y europeos no-15 en el municipio de Níjar (Almería)

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Montserrat Monserrat Hernández
Keyword(s):  
Secondary Schools ◽  
Social Integration ◽  
Educational Level ◽  
Household Income ◽  
Household Head ◽  
Religious Orders ◽  
Four Dimensions ◽  
The Social ◽  
The Family ◽  
Different Dimensions

Resumen: El objetivo principal de este artículo es comparar el proceso de integración social de los hijos de inmigrantes con dos procedencias dispares – africanos y europeos no pertenecientes a la Europa de los 15-, matriculados en los institutos de enseñanza secundaria en el municipio de Níjar (Almería). Concretamente vamos a analizar la adaptación de estos dos grupos en diferentes dimensiones: socioeconómica, relaciones mixtas, referentes culturales, normas, transnacionalidad y psicosocial. Los resultados se obtienen a partir de la administración de un cuestionario a todos los asistentes, ese día a clase, en el instituto de secundaria del municipio; resultando un total de 130 encuestas. Los datos muestran que existen diferencias en el proceso de integración entre ambos colectivos. Además del origen, hay otras variables que definen un proceso de integración diferenciada: nivel de estudios, ingresos familiares, profesión del cabeza de familia, etc. Lo que nos permite hablar de un caso de pluralismo fragmentado. Abstract: The main objective of this article is to compare the social integration of inmigrant children in two very differen sources –Africans and Europeans non-EU-15-, were enrolled in secondary schools in the municipality of Níjar (Almería). To do this, we will analyze the adaptation of these two groups in different dimensions: socioeconomic, mixer relationship, culture, norms, transnationality and psychosocial. The results obtained from the administration of a questionnaire to all attendees that there are differences between groups in the four dimensions and also the origins, there are other variables that are also highly influential as well as educational level, household income in the family, occupation of household head, the environment, the patterns of religious orders, etc. being able to talk like a fragmented pluralism.

PENGARUH PENDAPATAN RUMAH TANGGA TERHADAP KONSUMSI DAGING (SAPI, BABI DAN AYAM ) DI DESA SEA I KECAMATAN PINELENG

ZOOTEC ◽  
2014 ◽  
Vol 34 (2) ◽  
pp. 10
Author(s):  
Richie A.F. Osak ◽  
V V.J Panelewen ◽  
J. Pandey ◽  
I. D.R Lumenta
Keyword(s):  
Household Income ◽  
Household Head ◽  
Secondary Data ◽  
Meat Consumption ◽  
Research Problem ◽  
Chicken Meat ◽  
Primary Data ◽  
Survey Method ◽  
The Difference ◽  
The Village

ABSTRACT THE EFFECT OF HOUSEHOLD INCOME ON MEAT CONSUMPTION (BEEF, PORK AND CHIKEN) AT THE VILLAGE OF SEA I, PINELENG DISTRICT.This study aims to determine the magnitude of meat consumption (beef, porl and chiken) of household based on income levels in the Village of Sea I, Pineleng district and to determine the effect of household income on meat consumption (beef, porl and chiken) in the Village of Sea I, Pineleng district. Formulation of research problem is how much they purchased meat (beef, porl and chiken) consumption household in the Village of Sea I, Pineleng district. This study was conducted in the Village of Sea I, Pineleng district. Study was conducted using a survey method, and data were obtained through primary data and secondary data. Determination of the location (rural sample) in the study was conducted by purposive sampling method. Number of samples used in this study were 30 people. Data of this study were analyzed by descriptive and mathematical analysis methods. Income indicated the amount of income earned in a month household, whether they were from the household head or sourced from other household members who work and earn income. From the money earned, the highest number of respondents had incomes between 1.000.000 to 3.000.000/month with the percentage of 70 %, while the number of respondents with the smallest income was less than 1.000.000/month with the percentage of 16.67 %. The difference of income held by the respondents in the Village of Sea I, would have an impact on the amount of meat purchases each month. This was in accordance with the opinion Sukirno (2002) stating that most of the disposable income is used to buy food and clothing. Most of the meat consumed by people in the Village of Sea I was pork and chicken meat compared to beef, it was because the price of beef was relatively expensive compared to the price of pork and chicken meat. Based on research results, pork was the most meat consumed by family respondents about 21 families with the percentage of 70 % of respondents, followed by chicken meat about 18 families with the percentage of 60 % of respondents, and beef by 8 families with the percentage of 26 respondents, 67 % of domestic poultry and meat about 6 families with the percentage of 20 % of respondents. Based on the results of research, it can be concluded that household income significantly affect the consumption of meat in the Village of Sea I, Pineleng district and the average consumption of meat in the Village of Sea I, Pineleng district was about 8,9  kg/capita/year, below the national target of 10,3  kg/capita/year.   Key Words : Household income, meat consumption, Sea I Village.

scholarly journals Predictive modelling of soils’ hydraulic conductivity using artificial neural network and multiple linear regression

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Charles Gbenga Williams ◽  
Oluwapelumi O. Ojuri
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Hydraulic Conductivity ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Coarse Grained ◽  
Soil Types ◽  
Wide Range ◽  
Artificial Neural ◽  
Input Variables

AbstractAs a result of heterogeneity nature of soils and variation in its hydraulic conductivity over several orders of magnitude for various soil types from fine-grained to coarse-grained soils, predictive methods to estimate hydraulic conductivity of soils from properties considered more easily obtainable have now been given an appropriate consideration. This study evaluates the performance of artificial neural network (ANN) being one of the popular computational intelligence techniques in predicting hydraulic conductivity of wide range of soil types and compared with the traditional multiple linear regression (MLR). ANN and MLR models were developed using six input variables. Results revealed that only three input variables were statistically significant in MLR model development. Performance evaluations of the developed models using determination coefficient and mean square error show that the prediction capability of ANN is far better than MLR. In addition, comparative study with available existing models shows that the developed ANN and MLR in this study performed relatively better.

scholarly journals Non-Destructive Micromagnetic Determination of Hardness and Case Hardening Depth Using Linear Regression Analysis and Artificial Neural Networks

Metals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 18
Author(s):  
Rahel Jedamski ◽  
Jérémy Epp
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Regression Analysis ◽  
Artificial Neural Networks ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Case Hardening ◽  
Artificial Neural ◽  
Non Destructive

Non-destructive determination of workpiece properties after heat treatment is of great interest in the context of quality control in production but also for prevention of damage in subsequent grinding process. Micromagnetic methods offer good possibilities, but must first be calibrated with reference analyses on known states. This work compares the accuracy and reliability of different calibration methods for non-destructive evaluation of carburizing depth and surface hardness of carburized steel. Linear regression analysis is used in comparison with new methods based on artificial neural networks. The comparison shows a slight advantage of neural network method and potential for further optimization of both approaches. The quality of the results can be influenced, among others, by the number of teaching steps for the neural network, whereas more teaching steps does not always lead to an improvement of accuracy for conditions not included in the initial calibration.

scholarly journals 1412. The utility of respiratory viral panel testing for nosocomial fever in the neonatal intensive care unit

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S713-S713
Author(s):  
Carlo Fopiano Palacios ◽  
Eric Lemmon ◽  
James Campbell
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Linear Regression ◽  
Length Of Stay ◽  
Neonatal Intensive Care Unit ◽  
Neonatal Intensive Care ◽  
P Value ◽  
Fisher Exact Test ◽  
The Mean ◽  
Pcr Test

Abstract Background Patients in the neonatal intensive care unit (NICU) often develop fevers during their inpatient stay. Many neonates are empirically started on antibiotics due to their fragile clinical status. We sought to evaluate whether the respiratory viral panel (RVP) PCR test is associated with use of antibiotics in patients who develop a fever in the NICU. Methods We conducted a retrospective chart review on patients admitted to the Level 4 NICU of the University of Maryland Medical Center from November 2015 to June 2018. We included all neonates who developed a fever 48 hours into their admission. We collected demographic information and data on length of stay, fever work-up and diagnostics (including labs, cultures, RVP), and antibiotic use. Descriptive statistics, Fisher exact test, linear regression, and Welch’s ANOVA were performed. Results Among 347 fever episodes, the mean age of neonates was 72.8 ± 21.6 days, and 45.2% were female. Out of 30 total RVP samples analyzed, 2 were positive (6.7%). The most common causes of fever were post-procedural (5.7%), pneumonia (4.8%), urinary tract infection (3.5%), meningitis (2.6%), bacteremia (2.3%), or due to a viral infection (2.0%). Antibiotics were started in 208 patients (60%), while 61 neonates (17.6%) were already on antibiotics. The mean length of antibiotics was 7.5 ± 0.5 days. Neonates were more likely to get started on antibiotics if they had a negative RVP compared to those without a negative RVP (89% vs. 11%, p-value &lt; 0.0001). Patients with a positive RVP had a decreased length of stay compared to those without a positive RVP (30.3 ± 8.7 vs. 96.8 ± 71.3, p-value 0.01). On multivariate linear regression, a positive RVP was not associated with length of stay. Conclusion Neonates with a negative respiratory viral PCR test were more likely to be started on antibiotics for fevers. Respiratory viral PCR testing can be used as a tool to promote antibiotic stewardship in the NICU. Disclosures All Authors: No reported disclosures

Estimating Traffic Volume on Minor Roads at Rural Stop-Controlled Intersections using Deep Learning

2019 ◽  
Vol 2673 (4) ◽  
pp. 108-116 ◽  
Author(s):  
Mostafa H. Tawfeek ◽  
Karim El-Basyouny
Keyword(s):  
Neural Network ◽  
Linear Regression ◽  
Network Model ◽  
Neural Network Model ◽  
Deep Neural Network ◽  
Safety Management ◽  
Estimation Method ◽  
Estimation Model ◽  
The Neural Network ◽  
Annual Average Daily Traffic

Safety Performance Functions (SPFs) are regression models used to predict the expected number of collisions as a function of various traffic and geometric characteristics. One of the integral components in developing SPFs is the availability of accurate exposure factors, that is, annual average daily traffic (AADT). However, AADTs are not often available for minor roads at rural intersections. This study aims to develop a robust AADT estimation model using a deep neural network. A total of 1,350 rural four-legged, stop-controlled intersections from the Province of Alberta, Canada, were used to train the neural network. The results of the deep neural network model were compared with the traditional estimation method, which uses linear regression. The results indicated that the deep neural network model improved the estimation of minor roads’ AADT by 35% when compared with the traditional method. Furthermore, SPFs developed using linear regression resulted in models with statistically insignificant AADTs on minor roads. Conversely, the SPF developed using the neural network provided a better fit to the data with both AADTs on minor and major roads being statistically significant variables. The findings indicated that the proposed model could enhance the predictive power of the SPF and therefore improve the decision-making process since SPFs are used in all parts of the safety management process.

Social capital and national innovation system: a cross-country analysis

2014 ◽  
Vol 21 (4) ◽  
pp. 453-475 ◽  
Author(s):  
Sepehr Ghazinoory ◽  
Ali Bitaab ◽  
Ardeshir Lohrasbi
Keyword(s):  
Social Capital ◽  
National Level ◽  
Innovation System ◽  
Negative Effects ◽  
Content Type ◽  
Research Findings ◽  
Different Dimensions ◽  
The Impact ◽  
Positive Effect

Purpose – In the last two decades, researchers have paid much attention to the role of cultural values on economic and social development. In particular, the crucial role of different aspects of culture on the development of innovation has been stressed in the literature. Consequently, it is vital to understand how social capital, as a core cultural value, affects the innovation process and the innovative performance at the national level. However, to date, the impact of different dimensions of social capital and innovation has not been properly portrayed or explained. Thus, the purpose of this paper is to investigate the influence of four different dimensions of social capital (institutional and interpersonal, associational life and norms) on two of the main functions of national innovation system (NIS) (entrepreneurship and knowledge creation) based on over 50,000 observations in 34 countries. Design/methodology/approach – In this regard, national-level data from the World Values Survey database was employed to quantify social capital. Entrepreneurship is, in turn, assumed to consist of three sub-indexes and 14 indicators based on the Global Entrepreneurship Index. Knowledge creation is also measured through US Patent Office applications. Also, exploratory factor analysis and structural equation modeling approach were used to build the measurement model and investigate the impact that each factor of social capital had on entrepreneurship and knowledge application, respectively. Measurement and structural models were built and their reliability and validity were tested using various fit indices. Research findings suggest the strong positive effect of institutional trust and networking on entrepreneurship. Also, interpersonal trust and networks were shown to have high influence on knowledge development at the national level. Norms appear to have naïve to medium negative effects on both functions. Findings – Research findings suggest the strong positive effect of institutional trust and networking on entrepreneurship. Also, interpersonal trust and networks were shown to have high influence on knowledge development at the national level. Norms appear to have naïve to medium negative effects on both functions. Originality/value – However, to date, the impact of different dimensions of social capital and innovation has not been properly portrayed or explained.

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