Search results for: regression coefficients

Authors: Lalit Kumar, Rashid Al Shidi

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Phoenix dactylifera (date palm) is a major crop in many middle-eastern countries, including Oman. The Dubas bug Ommatissus lybicus is the main pest that affects date palm crops. However not all plantations are infested. It is still uncertain why some plantations get infested while others are not. This research investigated whether tree density and the system of planting (random versus systematic) had any relationship with infestation and levels of infestation. Remote Sensing and Geographic Information Systems were used to determine the density of trees (number of trees per unit area) while infestation levels were determined by manual counting of insects on 40 leaflets from two fronds on each tree, with a total of 20-60 trees in each village. The infestation was recorded as the average number of insects per leaflet. For tree density estimation, WorldView-3 scenes, with eight bands and 2m spatial resolution, were used. The Local maxima method, which depends on locating of the pixel of highest brightness inside a certain exploration window, was used to identify the trees in the image and delineating individual trees. This information was then used to determine whether the plantation was random or systematic. The ordinary least square regression (OLS) was used to test the global correlation between tree density and infestation level and the Geographic Weight Regression (GWR) was used to find the local spatial relationship. The accuracy of detecting trees varied from 83–99% in agricultural lands with systematic planting patterns to 50–70% in natural forest areas. Results revealed that the density of the trees in most of the villages was higher than the recommended planting number (120–125 trees/hectare). For infestation correlations, the GWR model showed a good positive significant relationship between infestation and tree density in the spring season with R² = 0.60 and medium positive significant relationship in the autumn season, with R² = 0.30. In contrast, the OLS model results showed a weaker positive significant relationship in the spring season with R² = 0.02, p < 0.05 and insignificant relationship in the autumn season with R² = 0.01, p > 0.05. The results showed a positive correlation between infestation and tree density, which suggests the infestation severity increased as the density of date palm trees increased. The correlation result showed that the density alone was responsible for about 60% of the increase in the infestation. This information can be used by the relevant authorities to better control infestations as well as to manage their pesticide spraying programs.

Keywords: dubas bug, date palm, tree density, infestation levels

Procedia PDF Downloads 191

Authors: Dana El-Mughayyar, Neil Manson, Erin Bigney, Eden Richardson, Dean Tripp, Edward Abraham

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Use of narcotics to treat pain has increased over the past two decades and is a contributing factor to the current public health crisis. Understanding the pre-operative risks of chronic narcotic use may be aided through investigation of psychological measures. The objective of the reported study is to determine predictors of narcotic use two years post-surgery in a thoracolumbar spine surgery population, including an array of psychological factors. A prospective observational study of 191 consecutively enrolled adult patients having undergone thoracolumbar spine surgery is presented. Baseline measures of interest included the Pain Catastrophizing Scale (PCS), Tampa Scale for Kinesiophobia, Multidimensional Scale for Perceived Social Support (MSPSS), Chronic Pain Acceptance Questionnaire (CPAQ-8), Oswestry Disability Index (ODI), Numeric Rating Scales for back and leg pain (NRS-B/L), SF-12’s Mental Component Summary (MCS), narcotic use and demographic variables. The post-operative measure of interest is narcotic use at 2-year follow-up. Narcotic use is collapsed into binary categories of use and no use. Descriptive statistics are run. Chi Square analysis is used for categorical variables and an ANOVA for continuous variables. Significant variables are built into a hierarchical logistic regression to determine predictors of post-operative narcotic use. Significance is set at α < 0.05. Results: A total of 27.23% of the sample were using narcotics two years after surgery. The regression model included ODI, NRS-Leg, time with condition, chief complaint, pre-operative drug use, gender, MCS, PCS subscale helplessness, and CPAQ subscale pain willingness and was significant χ² (13, N=191)= 54.99; p = .000. The model accounted for 39.6% of the variance in narcotic use and correctly predicted in 79.7% of cases. Psychological variables accounted for 9.6% of the variance over and above the other predictors. Conclusions: Managing chronic narcotic usage is central to the patient’s overall health and quality of life. Psychological factors in the preoperative period are significant predictors of narcotic use 2 years post-operatively. The psychological variables are malleable, potentially allowing surgeons to direct their patients to preventative resources prior to surgery.

Keywords: narcotics, psychological factors, quality of life, spine surgery

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Authors: Tausif A. Ishtiaque, Zarrin T. Tasin, Kazi S. Akter

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Current trend of urban expansion, especially in the developing countries has caused significant changes in land cover, which is generating great concern due to its widespread environmental degradation. Energy consumption of the cities is also increasing with the aggravated heat island effect. Distribution of land surface temperature (LST) is one of the most significant climatic parameters affected by urban land cover change. Recent increasing trend of LST is causing elevated temperature profile of the built up area with less vegetative cover. Gradual change in land cover, especially decrease in vegetative cover is enhancing the Urban Heat Island (UHI) effect in the developing cities around the world. Increase in the amount of urban vegetation cover can be a useful solution for the reduction of UHI intensity. LST and Normalized Difference Vegetation Index (NDVI) have widely been accepted as reliable indicators of UHI and vegetation abundance respectively. Chittagong, the second largest city of Bangladesh, has been a growth center due to rapid urbanization over the last several decades. This study assesses the intensity of UHI in Chittagong city by analyzing the relationship between LST and NDVI based on the type of land use/land cover (LULC) in the study area applying an integrated approach of Geographic Information System (GIS), remote sensing (RS), and regression analysis. Land cover map is prepared through an interactive supervised classification using remotely sensed data from Landsat ETM+ image along with NDVI differencing using ArcGIS. LST and NDVI values are extracted from the same image. The regression analysis between LST and NDVI indicates that within the study area, UHI is directly correlated with LST while negatively correlated with NDVI. It interprets that surface temperature reduces with increase in vegetation cover along with reduction in UHI intensity. Moreover, there are noticeable differences in the relationship between LST and NDVI based on the type of LULC. In other words, depending on the type of land usage, increase in vegetation cover has a varying impact on the UHI intensity. This analysis will contribute to the formulation of sustainable urban land use planning decisions as well as suggesting suitable actions for mitigation of UHI intensity within the study area.

Keywords: land cover change, land surface temperature, normalized difference vegetation index, urban heat island

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Authors: Keith T. S. Tung, H. W. Tsang, Rosa S. Wong, Frederick K. Ho, Patrick Ip

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Objectives: Atopic diseases are increasingly prevalent among children and adolescents, both locally and internationally. One of the possible contributing factors could be the hypercholesterolemia which leads to cholesterol accumulation in macrophages and other immune cells that would eventually promote inflammatory responses, including augmentation of toll-like receptor (TLR). Meanwhile, physical activity is well known for its beneficial effects against the condition of hypercholesterolemia and incidence of atopic diseases. This study, therefore, explored whether atopic diseases were associated with increased cholesterol levels and whether physical activity habit influenced this association. Methods: This is a sub-study derived from the longitudinal cohort study which recruited a group of children at five years of age in Kindergarten 3 (K3) to investigate the long-term impact of family socioeconomic status on child development. In 2018/19, adolescents (average age: 13 years old) were asked to report their physical activity habit and history of any atopic diseases. During health assessment, peripheral blood samples were collected from the adolescents to study their lipid profile [total cholesterol, high-density lipoprotein (HDL)-cholesterol, and low-density lipoprotein (LDL)-cholesterol]. Regression analyses were performed to test the relationships between variables of interest. Results: Among the 315 adolescents, 99 (31.4%) reported to have allergic rhinitis. There were 45 (14.3%) with eczema, 17 (5.4%) with a food allergy, and 12 (3.8%) with asthma. Regression analyses showed that adolescents with a history of any type of atopic diseases had significantly higher total cholesterol (B=13.3, p < 0.01) and LDL cholesterol (B=7.9, p < 0.05) levels. Further subgroup analyses were conducted to examine the effect of physical activity level on the association between atopic diseases and cholesterol levels. We found stronger associations among those who did not meet the World Health Organization recommendation of at least 60 minutes of moderate-to-vigorous activities each day (total cholesterol: B=15.5, p < 0.01; LDL cholesterol: B=10.4, p < 0.05). For those who met this recommendation, the associations between atopic diseases and cholesterol levels became insignificant. Conclusion: Our study results support the current research evidence on the relationship between an elevated level of cholesterol and atopic diseases. More importantly, our results provide preliminary support for the protective effect of regular exercises against elevated cholesterol level due to atopic diseases. The findings highlight the importance of a healthy lifestyle for keeping cholesterol levels in the normal range, which can bring benefits to both physical and mental health.

Keywords: atopic diseases, Chinese adolescents, cholesterol level, physical activity

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Authors: Sahar Jahani, Meryem Ayse Yucel, David Boas, Seyed Kamaledin Setarehdan

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Near-infrared spectroscopy allows monitoring of oxy- and deoxy-hemoglobin concentration changes associated with hemodynamic response function (HRF). HRF is usually affected by natural physiological hemodynamic (systemic interferences) which occur in all body tissues including brain tissue. This makes HRF extraction a very challenging task. In this study, we used Kalman filter based on a general linear model (GLM) of brain activity to define the proportion of systemic interference in the brain hemodynamic. The performance of the proposed algorithm is evaluated in terms of the peak to peak error (Ep), mean square error (MSE), and Pearson’s correlation coefficient (R2) criteria between the estimated and the simulated hemodynamic responses. This technique also has the ability of real time estimation of single trial functional activations as it was applied to classify finger tapping versus resting state. The average real-time classification accuracy of 74% over 11 subjects demonstrates the feasibility of developing an effective functional near infrared spectroscopy for brain computer interface purposes (fNIRS-BCI).

Keywords: hemodynamic response function, functional near-infrared spectroscopy, adaptive filter, Kalman filter

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Authors: Abdullah S. AlKhalifa, Mohammad Nasim Uddin, Michael Atkinson

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The primary objective of this investigation is to explore the aerodynamic impact of adding trailing edge serrations to a Wells turbine. The baseline turbine consists of eight blades with NACA 0015 airfoils. The blade chord length was 0.125 m, and the span was 0.100 m. Two modified NACA 0015 serrated configurations were studied: 1) full-span and 2) partial span serrations covering the trailing edge from hub to tip. Numerical simulations were carried out by solving the three-dimensional, incompressible steady-state Reynolds Averaged Navier-Stokes (RANS) equations using the k-ω SST turbulence model in ANSYS™ (CFX). The aerodynamic performance of the modified Wells turbine to the baseline was made by comparing non-dimensional parameters of torque coefficient, pressure drop coefficient, and turbine efficiency. A comparison of the surface limiting streamlines was performed to analyze the flow topology of the turbine blades. The trailing edge serrations generated a substantial change in surface pressure and effectively reduced the separated flow region, thus improving efficiency in most cases. As a result, the average efficiency increased across the range of simulated flow coefficients.

Keywords: renewable energy, trailing edge serrations, Wells turbine, partial serration

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Authors: Meghan E. Murray, Carri R. Tolmie

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This study aims to identify potential factors and widely applicable best practices that can contribute to improving corporate social responsibility (CSR) and corporate performance for firms by exploring the relationship between transformational leadership, spiritual intelligence, and emotional intelligence. Corporate social responsibility is when companies are cognizant of the impact of their actions on the economy, their communities, the environment, and the world as a whole while executing business practices accordingly. The prevalence of CSR has continuously strengthened over the past few years and is now a common practice in the business world, with such efforts coinciding with what stakeholders and the public now expect from corporations. Because of this, it is extremely important to be able to pinpoint factors and best practices that can improve CSR within corporations. One potential factor that may lead to improved CSR is spiritual intelligence (SQ), or the ability to recognize and live with a purpose larger than oneself. Spiritual intelligence is a measurable skill, just like emotional intelligence (EQ), and can be improved through purposeful and targeted coaching. This research project consists of two studies. Study 1 is a case study comparison of a benefit corporation and a non-benefit corporation. This study will examine the role of SQ and EQ as moderators in the relationship between the transformational leadership of employees within each company and the perception of each firm’s CSR and corporate performance. Project methodology includes creating and administering a survey comprised of multiple pre-established scales on transformational leadership, spiritual intelligence, emotional intelligence, CSR, and corporate performance. Multiple regression analysis will be used to extract significant findings from the collected data. Study 2 will dive deeper into spiritual intelligence itself by analyzing pre-existing data and identifying key relationships that may provide value to companies and their stakeholders. This will be done by performing multiple regression analysis on anonymized data provided by Deep Change, a company that has created an advanced, proprietary system to measure spiritual intelligence. Based on the results of both studies, this research aims to uncover best practices, including the unique contribution of spiritual intelligence, that can be utilized by organizations to help enhance their corporate social responsibility. If it is found that high spiritual and emotional intelligence can positively impact CSR effort, then corporations will have a tangible way to enhance their CSR: providing targeted employees with training and coaching to increase their SQ and EQ.

Keywords: corporate social responsibility, CSR, corporate performance, emotional intelligence, EQ, spiritual intelligence, SQ, transformational leadership

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Authors: Ploychompoo Kittikunchotiwut

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This study examines the relationships between human resource practices, knowledge management capacity, and innovation performance. The data were collected by using a questionnaire from 241 firms in the hotels in Thailand. The hypothesized relationships among variables are examined by using ordinary least square (OLS) regression analysis. The findings show that human resource practices have a positive effect on knowledge management capacity. Besides, knowledge management capacity was found to positively affect innovation performance. Finally, the limitations of the study and directions for future research are discussed.

Keywords: human resource practices, knowledge management capacity, innovation performance

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Authors: Jinliang Yuan, Jong-Sung Yu, Bengt Sundén

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A computational fluid dynamics (CFD) model is developed for rechargeable non-aqueous electrolyte lithium-air batteries with a partial opening for oxygen supply to the cathode. Multi-phase transport phenomena occurred in the battery are considered, including dissolved lithium ions and oxygen gas in the liquid electrolyte, solid-phase electron transfer in the porous functional materials and liquid-phase charge transport in the electrolyte. These transport processes are coupled with the electrochemical reactions at the active surfaces, and effects of discharge reaction-generated solid Li2O2 on the transport properties and the electrochemical reaction rate are evaluated and implemented in the model. The predicted results are discussed and analyzed in terms of the spatial and transient distribution of various parameters, such as local oxygen concentration, reaction rate, variable solid Li2O2 volume fraction and porosity, as well as the effective diffusion coefficients. It is found that the effect of the solid Li2O2 product deposited at the solid active surfaces is significant on the transport phenomena and the overall battery performance.

Keywords: Computational Fluid Dynamics (CFD), modeling, multi-phase, transport phenomena, lithium-air battery

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Authors: Chuyuan Wang, Nayan Khare, Lily Villa, Patricia Solis, Elizabeth A. Wentz

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Maricopa County, Arizona, has a semi-arid hot desert climate that is one of the hottest regions in the United States. The exacerbated urban heat island (UHI) effect caused by rapid urbanization has made the urban area even hotter than the rural surroundings. The Phoenix metropolitan area experiences extremely high temperatures in the summer from June to September that can reach the daily highest of 120 °F (48.9 °C). Morbidity and mortality due to the environmental heat is, therefore, a significant public health issue in Maricopa County, especially because it is largely preventable. Public records from the Maricopa County Department of Public Health (MCDPH) revealed that between 2012 and 2016, there were 10,825 incidents of heat-related morbidity incidents, 267 outdoor environmental heat deaths, and 173 indoor heat-related deaths. A lot of research has examined heat-related death and its contributing factors around the world, but little has been done regarding heat-related morbidity issues, especially for regions that are naturally hot in the summer. The objective of this study is to examine the demographic, socio-economic, housing, and environmental factors that contribute to heat-related morbidity in Maricopa County. We obtained heat-related morbidity data between 2012 and 2016 at census tract level from MCDPH. Demographic, socio-economic, and housing variables were derived using 2012-2016 American Community Survey 5-year estimate from the U.S. Census. Remotely sensed Landsat 7 ETM+ and Landsat 8 OLI satellite images and Level-1 products were acquired for all the summer months (June to September) from 2012 and 2016. The National Land Cover Database (NLCD) 2016 percent tree canopy and percent developed imperviousness data were obtained from the U.S. Geological Survey (USGS). We used ordinary least squares (OLS) regression analysis to examine the empirical relationship between all the independent variables and heat-related morbidity rate. Results showed that higher morbidity rates are found in census tracts with higher values in population aged 65 and older, population under poverty, disability, no vehicle ownership, white non-Hispanic, population with less than high school degree, land surface temperature, and surface reflectance, but lower values in normalized difference vegetation index (NDVI) and housing occupancy. The regression model can be used to explain up to 59.4% of total variation of heat-related morbidity in Maricopa County. The multiscale geographically weighted regression (MGWR) technique was then used to examine the spatially varying relationships between heat-related morbidity rate and all the significant independent variables. The R-squared value of the MGWR model increased to 0.691, that shows a significant improvement in goodness-of-fit than the global OLS model, which means that spatial heterogeneity of some independent variables is another important factor that influences the relationship with heat-related morbidity in Maricopa County. Among these variables, population aged 65 and older, the Hispanic population, disability, vehicle ownership, and housing occupancy have much stronger local effects than other variables.

Keywords: census, empirical modeling, heat-related morbidity, spatial analysis

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Authors: Vineel Inampudi, Arjun Prakash, Joseph Vinod

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Aims and Objectives: To evaluate the interrater reliability in grading ASPECTS score, between emergency medicine physician at first contact and radiologist among patients with acute ischemic stroke. Materials and Methods: We conducted a retrospective analysis of 86 acute ischemic stroke cases referred to the Department of Radiodiagnosis during November 2014 to January 2016. The imaging (plain CT scan) was performed using GE Bright Speed Elite 16 Slice CT Scanner. ASPECTS score was calculated separately by an emergency medicine physician and radiologist. Interrater reliability for total and dichotomized ASPECTS (≥ 6 and < 6) scores were assessed using statistical analysis (ICC and Cohen ĸ coefficients) on SPSS software (v17.0). Results: Interrater agreement for total and dichotomized ASPECTS was substantial (ICC 0.79 and Cohen ĸ 0.68) between the emergency physician and radiologist. Mean difference in ASPECTS between the two readers was only 0.15 with standard deviation of 1.58. No proportionality bias was detected. Bland Altman plot was constructed to demonstrate the distribution of ASPECT differences between the two readers. Conclusion: Substantial interrater agreement was noted in grading ASPECTS between emergency medicine physician at first contact and radiologist thereby confirming its robustness even in a rural setting.

Keywords: ASPECTS, computed tomography, MCA territory, stroke

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Authors: Emmanuel Carlo Belara, Albert John Dela Merced, Mark Anthony Dominguez, Diomari Erasga, Jerome Ferrer, Bernard Ombrog

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Social distancing errors are a common prevalence between vaccinated and unvaccinated in the Filipino community. This study aims to identify and relate the factors on how they affect our daily lives. Observed factors include memory, attention, anxiety, decision-making, and stress. Upon applying the ergonomic tools and statistical treatment such as t-test and multiple linear regression, stress and attention turned out to have the most impact to the errors of social distancing.

Keywords: vaccinated, unvaccinated, socoal distancing, filipinos

Procedia PDF Downloads 199

Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Halison da Silva Pereira, Ciro Sobrinho Campolina Martins, Vitor Mainenti Leal Lopes

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Long range performance is a goal for aircraft configuration optimization. Blended Wing Body (BWB) is presented in many works of literature as the most aerodynamically efficient design for a fixed-wing aircraft. Because of its high weight to thrust ratio, BWB is the ideal configuration for many Unmanned Aerial Vehicle (UAV) missions on geomatics applications. In this work, a BWB aerodynamic design for typical light geomatics payload is presented. Aerodynamic non-dimensional coefficients are predicted using low Reynolds number computational techniques (3D Panel Method) and wing parameters like aspect ratio, taper ratio, wing twist and sweep are optimized for high cruise performance and flight quality. The methodology of this work is a summary of tailless aircraft wing design and its application, with appropriate computational schemes, to light UAV subjected to low Reynolds number flows leads to conclusions like the higher performance and flight quality of thicker airfoils in the airframe body and the benefits of using aerodynamic twist rather than just geometric.

Keywords: blended wing body, low Reynolds number, panel method, UAV

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Authors: Hrvoje Simovic

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Paper analyses the key problems of fiscal sustainability in Croatia. To point out key challenges of fiscal sustainability, the public debt sustainability is analyzed using standard indicators of fiscal stability, accompanied with the identification of regime changes approach in the public debt trajectory using switching regression approach. The analysis is conducted for the period from 2001 to 2016. Results show huge vulnerability in recession period (2009-14), so key challenges in current fiscal policy and public debt management are recognized in maturity prolongation, interest rates trends, and credit rating expectations.

Keywords: fiscal sustainability, public debt, Croatia, budget deficit

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Authors: Omar Al Ali

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The current study was aimed to explore the relationships between emotional intelligence, cognitive ability, and leader's performance. Data were collected from 260 senior managers from UAE. The results showed that there are significant relationships between emotional intelligence and leadership performance as measured by the annual internal evaluations of each participant (r = .42, p < .01). Data from regression analysis revealed that both variables namely emotional intelligence (beta = .31, p < .01), and cognitive ability (beta = .29, p < .01), predicted leadership competencies, and together explained 26% of its variance. Data suggests that EI and cognitive ability are significantly correlated with leadership performance. In depth implications of the present findings for human resource development theory and practice are discussed.

Keywords: emotional intelligence, cognitive ability, leadership, performance

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Authors: Melisa Mete, Gary Davies, Susan Whelan

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Maintaining a good employer brand image is crucial for companies since it has numerous advantages such as better recruitment, retention and employee engagement, and commitment. This study aims to understand the relationship between employer brand image and employee satisfaction and engagement in the British context. A panel survey data (N=228) is tested via the regression models from the Hayes (2012) PROCESS macro, in IBM SPSS 23.0. The results are statistically significant and proves that the more positive employer brand image, the greater employee’ engagement and satisfaction, and the greater is employee satisfaction, the greater their engagement.

Keywords: employer brand, employer brand image, employee engagement, employee satisfaction

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Authors: Pavana Basavakumar, Devadas Bhat

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Diabetes is a disease which often goes undiagnosed until its secondary effects are noticed. Early detection of the disease is necessary to avoid serious consequences which could lead to the death of the patient. Conventional invasive tests for screening of diabetes are mostly painful, time consuming and expensive. There’s also a risk of infection involved, therefore it is very essential to develop non-invasive methods to screen and estimate the level of blood glucose. Extensive research is going on with this perspective, involving various techniques that explore optical, electrical, chemical and thermal properties of the human body that directly or indirectly depend on the blood glucose concentration. Thus, non-invasive blood glucose monitoring has grown into a vast field of research. In this project, an attempt was made to device a prototype for screening of diabetes by measuring electrical impedance of the skin and building a model to predict a patient’s condition based on the measured impedance. The prototype developed, passes a negligible amount of constant current (0.5mA) across a subject’s index finger through tetra polar silver electrodes and measures output voltage across a wide range of frequencies (10 KHz – 4 MHz). The measured voltage is proportional to the impedance of the skin. The impedance was acquired in real-time for further analysis. Study was conducted on over 75 subjects with permission from the institutional ethics committee, along with impedance, subject’s blood glucose values were also noted, using conventional method. Nonlinear regression analysis was performed on the features extracted from the impedance data to obtain a model that predicts blood glucose values for a given set of features. When the predicted data was depicted on Clarke’s Error Grid, only 58% of the values predicted were clinically acceptable. Since the objective of the project was to screen diabetes and not actual estimation of blood glucose, the data was classified into three classes ‘NORMAL FASTING’,’NORMAL POSTPRANDIAL’ and ‘HIGH’ using linear Support Vector Machine (SVM). Classification accuracy obtained was 91.4%. The developed prototype was economical, fast and pain free. Thus, it can be used for mass screening of diabetes.

Keywords: Clarke’s error grid, electrical impedance of skin, linear SVM, nonlinear regression, non-invasive blood glucose monitoring, screening device for diabetes

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Authors: Gaosheng Ju

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Our empirical evidence supports a model of consumption planning behaviors with the following two characteristics. First, households formulate a rational consumption target based on their desired target, displaying a diminishing sensitivity to the discrepancy between them. Second, the established target is a reference point for their planned consumption. The diminishing sensitivity leads to opposite reactions in higher and lower quantiles of both consumption targets and consumption growth to changes in economic conditions. This phenomenon accounts for the perplexingly low correlation between consumption and other macroeconomic variables. Furthermore, the opposing movements of consumption targets offer new insights into consumption-based asset pricing.

Keywords: consumption planning, reference point, diminishing sensitivity, quantile regression, asset pricing puzzles

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: R. Hashim, A. J. Bock, S. Cooper

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Absorptive capacity generally facilitates the adoption of innovation. How does this relationship change when economic return is not the sole driver of innovation uptake? We investigate whether absorptive capacity facilitates the adoption of green innovation based on a survey of 79 construction companies in Scotland. Based on the results of multiple regression analyses, we confirm that existing knowledge utilisation (EKU), knowledge building (KB) and external knowledge acquisition (EKA) are significant predictors of green process GP), green administrative (GA) and green technical innovation (GT), respectively. We discuss the implications for theories of innovation adoption and knowledge enhancement associated with environmentally-friendly practices.

Keywords: absorptive capacity, construction industry, environmental, green innovation

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Authors: Mohiuddin Ahsanul Kabir Chowdhury, Ahmed Ehsanur Rahman, Nazia Binte Ali, Abdullah Nurus Salam Khan, Afrin Iqbal, Mohammad Mehedi Hasan, Salma Morium, Afsana Bhuiyan, Shams El Arifeen

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Violence against women has been treated as a global epidemic which is as fatal as any serious disease or accidents. Like many other low-income countries it is also common in Bangladesh. In spite of existence of a few documented evidences in some other countries, in Bangladesh, domestic violence against women (DVAW) is not considered as a factor for malnutrition in children yet. Hence, the aim of the study was to investigate the association between DVAW and the nutritional status of their under-5 children in the context of slum areas of Chittagong, Bangladesh. A Cross-sectional survey was conducted among 87 women of reproductive age having at least one child under-5 years of age and staying with husband for at least last 1 year in selected slums under Chittagong City Corporation area. Data collection tools were structured questionnaire for the study participants and mid-upper arm circumference (MUAC) to measure the nutritional status of the under-5 children. The data underwent descriptive and regression analysis. Out of 87 respondents, 50 (57.5%) reported to suffer from domestic violence by their husband during last one year. Physical violence was found to be significantly associated with age (p=0.02), age at marriage (p=0.043), wealth score (p=0.000), and with knowledge regarding law (p=0.017). According to the measurement of mid-upper arm circumference (MUAC) 21% children were suffering from severe acute malnutrition (SAM) and the same percentage of children were suffering from moderate acute malnutrition (MAM). However, unadjusted odds ratio suggested that there was negative association with domestic violence and nutritional status. But, the logistic regression confounding for other variable showed significant association with total family income (p=0.006), wealth score (p=0.031), age at marriage (p=0.029) and number of child (p=0.006). Domestic violence against women and under nutrition of the children, both are highly prevalent in Bangladesh. More extensive research should be performed to identify the factors contributing to the high prevalence of domestic violence and malnutrition in urban slums of Bangladesh. Household-based intervention is needed to limit this burning problem. In a nutshell, effective community participation, education and counseling are essential to create awareness among the community.

Keywords: Bangladesh, cross sectional survey, domestic violence against women, nutritional status, under-5 children, urban slums

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Authors: Ceren Vardar Acar, Mine Caglar

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In finance, the price of a volatile asset can be modeled using fractional Brownian motion (fBm) with Hurst parameter H>1/2. The Black-Scholes model for the values of returns of an asset using fBm is given as, 〖Y_t=Y_0 e^((r+μ)t+σB)〗_t^H, 0≤t≤T where Y_0 is the initial value, r is constant interest rate, μ is constant drift and σ is constant diffusion coefficient of fBm, which is denoted by B_t^H where t≥0. Black-Scholes model can be constructed with some Markov processes such as Brownian motion. The advantage of modeling with fBm to Markov processes is its capability of exposing the dependence between returns. The real life data for a volatile asset display long-range dependence property. For this reason, using fBm is a more realistic model compared to Markov processes. Investors would be interested in any kind of information on the risk in order to manage it or hedge it. The maximum possible loss is one way to measure highest possible risk. Therefore, it is an important variable for investors. In our study, we give some theoretical bounds on the distribution of maximum possible loss of fBm. We provide both asymptotical and strong estimates for the tail probability of maximum loss of standard fBm and fBm with drift and diffusion coefficients. In the investment point of view, these results explain, how large values of possible loss behave and its bounds.

Keywords: maximum drawdown, maximum loss, fractional brownian motion, large deviation, Gaussian process

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Authors: Jasmine Latiolais

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Much of the disaster-related literature finds a positive relationship between the impact of a natural disaster and the growth of wages. Panel datasets are often used to explore these effects. However, natural disasters do not impact a single variable in the economy. Rather, natural disasters affect all facets of the economy, simultaneously, upon impact. It is difficult to control for all factors that would be influenced by the impact of a natural disaster, which can lead to lead to omitted variable bias in those studies employing panel datasets. To address this issue of omitted variable bias, an interrupted time series analysis is used to test the short-run relationship between the impact of Hurricanes Katrina and Rita on parish wage levels in Southern Louisiana, inherently controlling for economic conditions. This study provides evidence that natural disasters do increase wages in the very short term (one quarter following the impact of the hurricane) but that these results are not seen in the longer term and are not robust. In addition, the significance of the coefficients changes depending on the parish. Overall, this study finds that previous literature on this topic may not be robust when considered through a time-series lens.

Keywords: economic recovery, local economies, local wage growth, natural disasters

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Authors: Howard Gomwe, Eunice Seekoe, Philemon Lyoka, Chioneso Show Marange, Dennyford Mafa

Abstract:

There is arguably a lack of literature regarding body physical fitness and body composition amongst primary school learners in South Africa. For this reason, the study is aimed at investigating and accessing how body composition relates to physical fitness amongst primary school learners in the Eastern Cape Province of South Africa. In order to achieve this, a school-based cross-sectional survey was carried out among 876 primary school learners aged 9 to 14 years. Body composition indicators were measured and/or calculated, whilst physical fitness was evaluated according to the EUROFIT fitness standards by a 20 m shuttle run, push-ups, sit and reach as well as sit-ups. Out of 876 participants, a total of 870 were retained. Of these, 351 (40.34%) were boys, and 519 (59.66%) were girls. The average age of learners was 11.04 ± 1.50 years, with boys having a significantly (p = 0.002) higher mean age (M = 11.24; SD = 1.51 years) as compared to that of girls (M = 10.91; SD = 1.48 years). The non-parametric Spearman Rho correlation coefficients revealed several significant and negative relationships between body composition measurements with physical fitness characteristics, which were stronger in girls than in boys. The findings advocate for policymakers and responsible authorities to initiate the development of policies and interventions targeted at encouraging physical activity and health promotion among primary school learners in South Africa, especially in girls.

Keywords: BMI, body composition, body fat, children, physical fitness, primary school

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Authors: Kevin Anderson, Sukhwinder Singh Sandhu, Nouh Anies, Shilpa Ravichandra, Steven Dobbs, Donald Edberg

Abstract:

This paper presents the results of a Finite Element based vibration analysis of a solar powered Unmanned Aerial Vehicle (UAV). The purpose of this paper was to quantify the free vibration, forced vibration response due to differing point inputs in order to mimic the vibration induced by actuators (magnet in coil generators) used to aid in the flight of the UAV. A Fluid-Structure Interaction (FSI) study was performed in order to ascertain pertinent deigns stresses and deflections as well as aerodynamic parameters of the UAV airfoil. The 10 ft span airfoil is modeled using Mylar as the primary material. Results show that the free mode in bending is 4.8 Hz while the first forced bending mode is in the range of 16.2 to 16.7 Hz depending on the location of excitation. The free torsional bending mode is 28.3 Hz, and the first forced torsional mode is in the range of 26.4 to 27.8 Hz, depending on the location of excitation. The FSI results predict the coefficients of aerodynamic drag and lift of 0.0052 and 0.077, respectively, which matches hand-calculations used to validate the Finite Element based results. FSI based maximum von Mises stresses and deflections were found to be 0.282 MPa and 3.4 mm, respectively. Dynamic pressures on the airfoil range of 1.04 to 1.23 kPa corresponding to velocity magnitudes in the range of 22 to 66 m/s.

Keywords: ANSYS, finite element, FSI, UAV, vibrations

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Authors: Ahmed R. Abdelaziz, Zaki M. I. Osha

Abstract:

Solar radiation data are of great significance for solar energy system design. This study aims at developing and calibrating new empirical models for estimating monthly mean daily global solar radiation on a horizontal surface in Alexandria, Egypt. Day length hours, sun height, day number, and declination angle calculated data are used for this purpose. A comparison between measured and calculated values of solar radiation is carried out. It is shown that all the proposed correlations are able to predict the global solar radiation with excellent accuracy in Alexandria.

Keywords: solar energy, global solar radiation, model, regression coefficient

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Authors: Hoda Aleali, Nastran Mansour, Maryam Mirzaie

Abstract:

In this paper, we study the optical nonlinearities of Silver sulfide (Ag2S) nanostructures dispersed in the Dimethyl sulfoxide (DMSO) under exposure to 532 nm, 15 nanosecond (ns) pulsed laser irradiation. Ultraviolet–visible absorption spectrometry (UV-Vis), X-ray diffraction (XRD), and transmission electron microscopy (TEM) are used to characterize the obtained nanocrystal samples. The band gap energy of colloid is determined by analyzing the UV–Vis absorption spectra of the Ag2S NPs using the band theory of semiconductors. Z-scan technique is used to characterize the optical nonlinear properties of the Ag2S nanoparticles (NPs). Large enhancement of two photon absorption effect is observed with increase in concentration of the Ag2S nanoparticles using open Z-scan measurements in the ns laser regime. The values of the nonlinear absorption coefficients are determined based on the local nonlinear responses including two photon absorption. The observed aperture dependence of the Ag2S NP limiting performance indicates that the nonlinear scattering plays an important role in the limiting action of the sample.The concentration dependence of the optical liming is also investigated. Our results demonstrate that the optical limiting threshold decreases with increasing the silver sulfide NPs in DMSO.

Keywords: nanoscale materials, silver sulfide nanoparticles, nonlinear absorption, nonlinear scattering, optical limiting

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Authors: Muqaddas Javed, Muhammad Hanif

Abstract:

The generalized multivariate ratio and regression type estimators for population mean are suggested under multi-phase stratified systematic sampling (MPSSS) using multi auxiliary information. Estimators are developed under the two different situations of availability of auxiliary information. The expressions of bias and mean square error (MSE) are developed. Special cases of suggested estimators are also discussed and simulation study is conducted to observe the performance of estimators.

Keywords: generalized estimators, multi-phase sampling, stratified random sampling, systematic sampling

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Authors: Woledegebrieal Aregay

Abstract:

Introduction: Family planning is defined as the ability of individuals and couples to anticipate and attain their desired number of children and the spacing and timing of their births. It is part of a strategy to reduce poverty, maternal, infant and child mortality; empowers women by lightening the burden of excessive childbearing. Family planning is achieved through the use of different contraceptive methods among which the most effective method is modern family planning methods like Long-Acting Reversible Contraceptive (LARCs) which are IUCD and Implant and these methods have multiple advantages over other reversible methods. Most importantly, once in place, they do not require maintenance and their duration of action is long, ranging from 3 to10 years. Methods: An institutional-based cross-sectional study was conducted in Gondar town among female college students from April-May. A simple random sampling technique was employed to recruit a total of 1166 study subjects. Descriptive variables were computed for all predictors & dependent variables. The presence of an association between covariates & LARC use was observed by two tables’ findings using the chi-square test. Bivariate logistic regression was conducted to identify all possible factors affecting LARC utilization & its crude Odds Ratio, 95% Confidence Interval (CI) & P-value was observed. A multivariable logistic regression model was developed to control possible confounding variables. Adjusted Odds Ratio (AOR) with 95% Confidence Interval (CI) &P-values will be computed to identify significantly associated factors (P < 0.05) with LARC utilization. Result: Utilization of LARCs was 20.4%, the most common is Implant 86(96.5%), and followed by Intra-Uterine Contraceptive Device (IUCD) 3(3.5%). The result of the multivariate analysis revealed that the significant association of marital status of the respondent on utilization of LARC [AOR 3.965(2.051-7.665)], discussion of the respondent about LARC utilization with the husband/boyfriend [AOR 2.198(1.191-4.058)], and attitude of the respondent on implant was found to be associated [AOR 0.365(0.143-0.933)].Conclusion: The level of knowledge and attitude in this study was not satisfactory, the utilization of long-acting reversible contraceptives among college students was relatively satisfactory but if the knowledge and attitude of the participant has improved the prevalence of LARC were increased.

Keywords: utilization, long-acting reversible contraceptive, Ethiopia, Gondar

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