Search results for: impact models

Authors: Christian Bruss, Simona Gamba, Davide Azzolini, Federico Podestà

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In this paper, the authors assess the impact of different political and environmental shocks on the size and on the age and gender composition of asylum-related migration flows to Europe. With this paper, the authors contribute to the literature by looking at the impact of different political and environmental shocks on the gender and age composition of migration flows in addition to the size of these flows. Conflicting theories predict different outcomes concerning the relationship between political and environmental shocks and the migration flows composition. Analyzing the relationship between the causes of migration and the composition of migration flows could yield more insights into the mechanisms behind migration decisions. In addition, this research may contribute to better informing national authorities in charge of receiving these migrant, as women and children/the elderly require different assistance than young men. To be prepared to offer the correct services, the relevant institutions have to be aware of changes in composition based on the shock in question. The authors analyze the effect of different types of shocks on the number, the gender and age composition of first time asylum seekers originating from 154 sending countries. Among the political shocks, the authors consider: violence between combatants, violence against civilians, infringement of political rights and civil liberties, and state terror. Concerning environmental shocks, natural disasters (such as droughts, floods, epidemics, etc.) have been included. The data on asylum seekers applying to any of the 32 Schengen Area countries between 2008 and 2015 is on a monthly basis. Data on asylum applications come from Eurostat, data on shocks are retrieved from various sources: georeferenced conflict data come from the Uppsala Conflict Data Program (UCDP), data on natural disasters from the Centre for Research on the Epidemiology of Disasters (CRED), data on civil liberties and political rights from Freedom House, data on state terror from the Political Terror Scale (PTS), GDP and population data from the World Bank, and georeferenced population data from the Socioeconomic Data and Applications Center (SEDAC). The authors adopt a Difference-in-Differences identification strategy, exploiting the different timing of several kinds of shocks across countries. The highly skewed distribution of the dependent variable is taken into account by using count data models. In particular, a Zero Inflated Negative Binomial model is adopted. Preliminary results show that different shocks - such as armed conflict and epidemics - exert weak immediate effects on asylum-related migration flows and almost non-existent effects on the gender and age composition. However, this result is certainly affected by the fact that no time lags have been introduced so far. Finding the correct time lags depends on a great many variables not limited to distance alone. Therefore, finding the appropriate time lags is still a work in progress. Considering the ongoing refugee crisis, this topic is more important than ever. The authors hope that this research contributes to a less emotionally led debate.

Keywords: age, asylum, Europe, forced migration, gender

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Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a promising and cost effective alternative to conventional treatment systems that facilitates direct oxidation of ammonium nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of any external carbon sources. The present study investigates the process kinetics of laboratory scale anammox hybrid reactor (AHR) which combines the dual advantages of attached and suspended growth. The performance & behaviour of AHR was studied under varying hydraulic retention time (HRTs) and nitrogen loading rate (NLRs). The experimental unit consisted of 4 numbers of 5L capacity anammox hybrid reactor inoculated with mixed seed culture containing anoxic and activated sludge. Pseudo steady state (PSS) ammonium and nitrite removal efficiencies of 90.6% and 95.6%, respectively, were achieved during acclimation phase. After establishment of PSS, the performance of AHR was monitored at seven different HRTs of 3.0, 2.5, 2.0, 1.5, 1.0, 0.5 and 0.25 d with increasing NLR from 0.4 to 4.8 kg N/m3d. The results showed that with increase in NLR and decrease in HRT (3.0 to 0.25 d), AHR registered appreciable decline in nitrogen removal efficiency from 92.9% to 67.4 %, respectively. The HRT of 2.0 d was considered optimal to achieve substantial nitrogen removal of 89%, because on further decrease in HRT below 1.5 days, remarkable decline in the values of nitrogen removal efficiency were observed. Analysis of data indicated that attached growth system contributes an additional 15.4 % ammonium removal and reduced the sludge washout rate (additional 29% reduction). This enhanced performance may be attributed to 25% increase in sludge retention time due to the attached growth media. Three kinetic models, namely, first order, Monod and Modified Stover-Kincannon model were applied to assess the substrate removal kinetics of nitrogen removal in AHR. Validation of the models were carried out by comparing experimental set of data with the predicted values obtained from the respective models. For substrate removal kinetics, model validation revealed that Modified Stover-Kincannon is most precise (R2=0.943) and can be suitably applied to predict the kinetics of nitrogen removal in AHR. Lawrence and McCarty model described the kinetics of bacterial growth. The predicted value of yield coefficient and decay constant were in line with the experimentally observed values.

Keywords: anammox, kinetics, modelling, nitrogen removal, sludge wash out rate, AHR

Procedia PDF Downloads 317

Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: A. Mudau, T. R. Stacey, R. A. Govender

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This paper reports for the first time the findings on the dynamic compressive strength data of Bushveld Complex brittle rock materials. These rocks were subjected to both quasi-static and impact loading tests to help understand their behaviour both under quasi-static and dynamic loading conditions. Unlike quasi-static tests, characterization of dynamic behaviour of materials is challenging, in particularly brittle rock materials. The split Hopkinson pressure bar (SHPB) results reported for anorthosite and norite showed relatively low values for dynamic compressive strength compared to the quasi-static uniaxial compressive strength data. It was noticed that the dynamic stress conditions were not fully attained during testing, as well as constant strain rate.

Keywords: Bushveld Complex, dynamic comperession, rock brittleness, stress equilibrium

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Authors: Aisha Bano, Rizwan Nazir

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The present study aimed at exploring the impact of meaning in life on psychological well-being and stress among university students. Victor Frankl's paradigm provided the theoretical foundation for this study. A sample of 560 university students was drawn from Quaid-i-Azam University Islamabad. The sample was drawn using stratified random sampling technique. Data were collected using Existence Scale, Warwick-Edinburg Mental Well-Being Scale, and Stress Scale. Results of linear regression analysis reveals that high perception of meaning in life will lead to high psychological well-being and low stress among university students. Non-significant differences are found on meaning in life variable with regard to gender in the sample using t-test. Together these results suggest that meaning in life independent of gender, is a significant predictor of the levels of stress and psychological well-being being directly related to psychological well-being and inversely related to stress levels.

Keywords: existential meaning in life, psychological well-being, stress, students

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Authors: Scarlet Tabot Enanga Longsti

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Community-Based Health Insurance (CBHI) schemes have been proposed as a possible means to achieve affordable health care in low-and lower-middle-income countries. The existing evidence provides mixed results on the impact of CBHI schemes on healthcare utilisation and out -of-pocket payments (OOPP) for healthcare. Over 900 CBHI schemes have been implemented in underdeveloped countries, and these schemes have undergone different modifications over the years. Prior reviews have suggested that different designs of CBHI schemes may result in different outcomes. Objectives: This review sought to determine the interventions that affect the impact of CBHI schemes on OOPP and health service utilisation. Interventions in this study referred to any action or modification in the design of a CBHI scheme that affected the impact of the scheme on OOPP and/or healthcare utilization. Methods: Any CBHI study that was done in a lower middle-income country, that used an experimental design, that included OOPP or health care utilisation as outcome variables, and that was published in either English or French was included in this study. Studies were searched for in MEDLINE, Embase, CINAHL, EconLit, IBSS, Web of Science, Cochrane Library, and Global Index Medicus from July to August 2023. Bias was assessed using Joanna Brigs Institute tools for quality assessment for randomized control trials and quasi experimental studies. A narrative synthesis was done. Results: 12 studies were included in the review, with a total of 69 villages, 13,653 households, and 62,786 participants. Average premium collection was 4.8 USD/year. Most CBHI schemes had flat rates. The study revealed that a range of interventions impact OOPP and health care utilisation. Five categories of interventions were identified. The intervention with the highest impact on OOPP and utilisation was “Audit visits”. Next in line came external funds, training scheme workers, and engaging community leaders and village heads to advertise the scheme. Free healthcare led to a significant increase in utilisation of health services, a significant reduction in Catastrophic health expenditure, but an insignificant effect on OOPP among insured compared with uninsured. Conclusions: Community-Based Health Insurance could pave the way for Universal Health Care in low and middle-income countries. However, this can only be possible if careful thought is given to how schemes are designed. Due to the heterogeneity of studies and results on CBHI schemes, there is need for further research for more effective designs to be developed.

Keywords: community based health insurance, developing countries, health service utilisation, out of pocket payment

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

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Authors: Gifty Kumadey, Albert Tchey Agbenyegah

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(i) Overview and research goal(s): This study aims to address research gaps in the Ghanaian pharmaceutical industry by examining the impact of environmental supply chain management (ESCM) practices on environmental and operational performance. Previous studies have provided inconclusive evidence on the relationship between ESCM practices and environmental and operational performance. The research aims to provide a clearer understanding of the impact of ESCM practices on environmental and operational performance in the context of the Ghanaian pharmaceutical industry. Limited research has been conducted on ESCM practices in developing countries, particularly in Africa. The study aims to bridge this gap by examining the drivers and barriers specific to the pharmaceutical industry in Ghana. The research aims to analyze the impact of ESCM practices on the achievement of Sustainable Development Goals (SDGs) in the Ghanaian pharmaceutical industry, focusing on SDGs 3, 12, 13, and 17. It also explores the potential for partnerships and collaborations to advance ESCM practices in the pharmaceutical industry. The research hypotheses suggest that pressure from stakeholder positively influences the adoption of ESCM practices in the Ghanaian pharmaceutical industry. By addressing these goals, the study aims to contribute to sustainable development initiatives and offer practical recommendations to enhance ESCM A practices in the industry. (ii) Research methods and data: This study uses a quantitative research design to examine the drivers and barriers to environmental supply chain management in the pharmaceutical industry in Accra.The sample size is approximately 150 employees, with senior and middle-level managers from pharmaceutical industry of Ghana. A purposive sampling technique is used to select participants with relevant knowledge and experience in environmental supply chain management. Data will be collected using a structured questionnaire using Likert scale responses. Descriptive statistics will be used to analyze the data and provide insights into current practices and their impact on environmental and operational performance. (iii) Preliminary results and conclusions: Main contributions: Identifying drivers/barriers to ESCM in Ghana's pharmaceutical industry, evaluating current ESCM practices, examining impact on performance, providing practical insights, contributing to knowledge on ESCM in Ghanaian context. The research contributes to SDGs 3, 9, and 12 by promoting sustainable practices and responsible consumption in the industry. The study found that government rules and regulations are the most critical drivers for ESCM adoption, with senior managers playing a significant role. However, employee and competitor pressures have a lesser impact. The industry has made progress in implementing certain ESCM practices, but there is room for improvement in areas like green distribution and reverse logistics. The study emphasizes the importance of government support, management engagement, and comprehensive implementation of ESCM practices in the industry. Future research should focus on overcoming barriers and challenges to effective ESCM implementation.

Keywords: environmental supply chain, sustainable development goal, ghana pharmaceutical industry, government regulations

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Authors: Siti Sabariah Buhari, Ruzita Abdul Talib, Poh Bee Koon

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This study aims to develop and evaluate an intervention to improve eating habits, active lifestyle and weight status of overweight and obese children in Negeri Sembilan. The H.E.B.A.T! Program involved children, parents, and school and focused on behaviour and environment modification to achieve its goal. The intervention consists of H.E.B.A.T! Camp, parent’s workshop and school-based activities. A total of 21 children from intervention school and 22 children from control school who had BMI for age Z-score ≥ +1SD participated in the study. Mean age of subjects was 10.8 ± 0.3 years old. Four phases were included in the development of the intervention. Evaluation of intervention was conducted through process, impact and outcome evaluation. Process evaluation found that intervention program was implemented successfully with minimal modification and without having any technical problems. Impact and outcome evaluation was assessed based on dietary intake, average step counts, BMI for age z-score, body fat percentage and waist circumference at pre-intervention (T0), post-intervention 1 (T1) and post-intervention 2 (T2). There was significant reduction in energy (14.8%) and fat (21.9%) intakes (at p < 0.05) at post-intervention 1 (T1) in intervention group. By controlling for sex as covariate, there was significant intervention effect for average step counts, BMI for age z-score and waist circumference (p < 0.05). In conclusion, the intervention made an impact on positive behavioural intentions and improves weight status of the children. It is expected that the HEBAT! Program could be adopted and implemented by the government and private sector as well as policy-makers in formulating childhood obesity intervention.

Keywords: childhood obesity, diet, obesity intervention, physical activity

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Authors: Marco Antonio Lara De la Calleja, María Catalina Ovando Chico, Eduardo Lopez Ruiz

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Community empowerment has been proved to be a key element in the solution of the food security problem. As a result of a conceptual analysis, it was found that agricultural production, economic development and governance, are the traditional basis of food security models. Although the literature points to social inclusion as an important factor for food security, no model has considered it as the basis of it. The aim of this research is to identify different dimensions that make an integral model for food security, with emphasis on community empowerment. A diagnosis was made in the study community (Tatoxcac, Zacapoaxtla, Puebla), to know the aspects that impact the level of food insecurity. With a statistical sample integrated by 200 families, the Latin American and Caribbean Food Security Scale (ELCSA) was applied, finding that: in households composed by adults and children, have moderated food insecurity, (ELCSA scale has three levels, low, moderated and high); that result is produced mainly by the economic income capacity and the diversity of the diet on its food. With that being said, a model was developed to promote food security through five dimensions: 1. Regional context of the community; 2. Structure and system of local food; 3. Health and nutrition; 4. Information and technology access; and 5. Self-awareness and empowerment. The specific actions on each axis of the model, allowed a systemic approach needed to attend food security in the community, through the empowerment of society. It is concluded that the self-awareness of local communities is an area of extreme importance, which must be taken into account for participatory schemes to improve food security. In the long term, the model requires the integrated participation of different actors, such as government, companies and universities, to solve something such vital as food security.

Keywords: community empowerment, food security, model, systemic approach

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Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

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Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

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Authors: Exa Heydemans, Jessica Sjah, Dwinanti Rika Marthanty

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This paper presents numerical simulations using an open boundary algorithm with modified dynamic boundary condition (mDBC) for weakly compressible smoothed particle hydrodynamics models from particle-based code Dualsphysics. The problems of piping erosion in dams and dikes are aimed for studying the algorithm. The case 2D model of unsteady fluid flow past around a fixed cylinder is simulated, where various values of Reynold’s numbers (Re40, Re60, Re80, and Re100) and different model’s resolution are considered. A constant velocity with different values of viscosity for generating various Reynold’s numbers and different numbers of particles over a cylinder for the resolution are modeled. The interaction between solid particles of the cylinder and fluid particles is concerned. The cylinder is affected by the hydrodynamics force caused by the flow of fluid particles. The solid particles of the cylinder are the observation points to obtain force and pressure due to the hydrodynamics forces. As results of the simulation, which is to show the capability to model 2D unsteady with various Reynold’s numbers, the pressure coefficient, drag coefficient, lift coefficient, and Strouhal number are compared to the previous work from literature.

Keywords: hydrodynamics, internal erosion, dualsphysics, viscous fluid flow

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Authors: Ying Li, Zaisheng Hong, Weihong Wang

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With the rapid enlargement of the size of Chinese universities, newly built campuses are springing up everywhere in recent years. It is urged to build eco-green campus because the role of higher education institutions in the transition to a more sustainable society has been highlighted for almost three decades. On condition that a new campus is usually built on an undeveloped site, where the basic infrastructure is not completed, finding proper strategies in planning and design of the campus becomes a primary concern. Low Impact Development (LID) options have been proposed as an alternative approach to make better use of rainwater in planning and design of an undeveloped site. On the basis of analyzing the natural circumstance, geographic condition, and other relative information, four main LID approaches are coordinated in this study of Hebei Union University, which are ‘Storage’, ‘Retaining’, ‘Infiltration’ and ‘Purification’. ‘Storage’ refers to a big central lake in the campus for rainwater harvesting. ‘Retaining’ means rainwater gardens scattered in the campus, also being known as bioretention areas which mimic the naturally created pools of water, to decrease surface flow runoff. ‘Infiltration’ is designed of grassed swales, which also play a part of floodway channel. ‘Purification’ is known as either natural or artificial wetland to reduce pollutants such as nitrogen and phosphorous in the waterbody. With above mentioned measures dealing with the synthetic use of rainwater in the acid & alkali area in the coastal district, an eco-green campus construction and an ecological sustainability will be realized, which will give us more enlightenment and reference.

Keywords: newly built campus, low impact development, planning design, rainwater reuse

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Authors: Emmanuel Iyamuremye

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Extreme rainfall events have caused significant damage to agriculture, ecology, and infrastructure, disruption of human activities, injury, and loss of life. They also have significant social, economic, and environmental consequences because they considerably damage urban as well as rural areas. Early detection of extreme maximum rainfall helps to implement strategies and measures, before they occur, hence mitigating the consequences. Extreme value theory has been used widely in modeling extreme rainfall and in various disciplines, such as financial markets, the insurance industry, failure cases. Climatic extremes have been analyzed by using either generalized extreme value (GEV) or generalized Pareto (GP) distributions, which provides evidence of the importance of modeling extreme rainfall from different regions of the world. In this paper, we focused on Peak Over Thresholds approach, where the Poisson-generalized Pareto distribution is considered as the proper distribution for the study of the exceedances. This research also considers the use of the generalized Pareto (GP) distribution with a Poisson model for arrivals to describe peaks over a threshold. The research used statistical techniques to fit models that used to predict extreme rainfall in Kigali. The results indicate that the proposed Poisson-GP distribution provides a better fit to maximum monthly rainfall data. Further, the Poisson-GP models are able to estimate various return levels. The research also found a slow increase in return levels for maximum monthly rainfall for higher return periods, and further, the intervals are increasingly wider as the return period is increasing.

Keywords: exceedances, extreme value theory, generalized Pareto distribution, Poisson generalized Pareto distribution

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Authors: Michelle Eliane Hernández-García, Angélica Lozano

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The traffic accidents study usually contemplates the relation between factors such as the type of vehicle, its operation, and the road infrastructure. Traffic accidents can be explained by different factors, which have a greater or lower relevance. Two zones are studied, a mixed industrial zone and the extended zone of it. The first zone has mainly residential (57%), and industrial (23%) land uses. Trucks are mainly on the roads where industries are located. Four sensors give information about traffic and speed on the main roads. The extended zone (which includes the first zone) has mainly residential (47%) and mixed residential (43%) land use, and just 3% of industrial use. The traffic mix is composed mainly of non-trucks. 39 traffic and speed sensors are located on main roads. The traffic mix in a mixed land use zone, could be related to traffic accidents. To understand this relation, it is required to identify the elements of the traffic mix which are linked to traffic accidents. Models that attempt to explain what factors are related to traffic accidents have faced multiple methodological problems for obtaining robust databases. Poisson regression models are used to explain the accidents. The objective of the Poisson analysis is to estimate a vector to provide an estimate of the natural logarithm of the mean number of accidents per period; this estimate is achieved by standard maximum likelihood procedures. For the estimation of the relation between traffic accidents and the traffic mix, the database is integrated of eight variables, with 17,520 observations and six vectors. In the model, the dependent variable is the occurrence or non-occurrence of accidents, and the vectors that seek to explain it, correspond to the vehicle classes: C1, C2, C3, C4, C5, and C6, respectively, standing for car, microbus, and van, bus, unitary trucks (2 to 6 axles), articulated trucks (3 to 6 axles) and bi-articulated trucks (5 to 9 axles); in addition, there is a vector for the average speed of the traffic mix. A Poisson model is applied, using a logarithmic link function and a Poisson family. For the first zone, the Poisson model shows a positive relation among traffic accidents and C6, average speed, C3, C2, and C1 (in a decreasing order). The analysis of the coefficient shows a high relation with bi-articulated truck and bus (C6 and the C3), indicating an important participation of freight trucks. For the expanded zone, the Poisson model shows a positive relation among traffic accidents and speed average, biarticulated truck (C6), and microbus and vans (C2). The coefficients obtained in both Poisson models shows a higher relation among freight trucks and traffic accidents in the first industrial zone than in the expanded zone.

Keywords: freight transport, industrial zone, traffic accidents, traffic mix, trucks

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Authors: Rabea Alfahad

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Learning English academic vocabulary poses a challenge on learning English.In this study, we harnessed interactive web-based e-books, and usedgamification and collaborative responsive writingto teach English academic vocabulary. We recruited 50 international students to investigate the impact of gamification on the participants’ learning gains. In so doing, the participants were randomly assigned to two groups: one group learned English academic vocabulary with gamification, and the second group learnedthem with traditional instructional methods. We used a pre/posttest to gauge the students’ cognitive attainment. We then administered independent samples t-test to find out the impact of gamification on learning academic vocabulary. We also employed an IMMS to collect data regarding the motivational level of the students. We administered a MANOVA test to measure the motivational level of the students in both groups. The results of this study suggested that …

Keywords: english language learners, technologhy integration, teaching, gamification

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Hongbin Yang, Mingxue Liao, Changwen Zheng, Mengyao Kong, Chaohui Liu

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Microfacet-based reflection models are widely used to model light reflections for rough surfaces. Microfacet models have become the standard surface material building block for describing specular components with varying roughness; and yet, while they possess many desirable properties as well as produce convincing results, their design ignores important sources of scattering, which can cause a significant loss of energy. Specifically, they only simulate the single scattering on the microfacets and ignore the subsequent interactions. As the roughness increases, the interaction will become more and more important. So a multiple-scattering microfacet model based on specular V-cavity is presented for this important open problem. However, it spends much unnecessary rendering time because of setting the same number of scatterings for different roughness surfaces. In this paper, we design a geometric attenuation term G to compute the BRDF (Bidirectional reflection distribution function) of multiple scattering of rough surfaces. Moreover, we consider determining the number of scattering by deterministic heuristics for different roughness surfaces. As a result, our model produces a similar appearance of the objects with the state of the art model with significantly improved rendering efficiency. Finally, we derive a multiple scattering BRDF based on the original microfacet framework.

Keywords: bidirectional reflection distribution function, BRDF, geometric attenuation term, multiple scattering, V-cavity model

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Authors: Moeen Naseer Butt

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Clustering –geographic concentrations of entities– has recently received more attention in marketing research and has been shown to affect multiple outcomes. This study investigates the impact of intrabrand clustering (clustering of same-brand outlets) on an outlet’s quality performance. Further, it assesses the moderating effects of interbrand clustering (clustering of other-brand outlets) and firm size. An examination of approximately 21,000 food service establishments in New York State in 2019 finds that the impact of intrabrand clustering on an outlet’s quality performance is context-dependent. Specifically, intrabrand clustering decreases, whereas interbrand clustering and firm size help increase the outlet’s performance. Additionally, this study finds that the role of firm size is more substantial than interbrand clustering in mitigating the adverse effects of intrabrand clustering on outlet quality performance.

Keywords: intraband clustering, interbrand clustering, firm size, brand competition, outlet performance, quality violations

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Authors: Panida Jongsuksomsakul

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This study of the ‘happiness’ and ‘sustainability’ in the community of Donkeaw, Amphoe Mae Rim, Chiang Mai Province during the non-election period in Thailand, noted that their happiness levels are in the middle-average range. This was found using a mixed approach of qualitative and quantitative methods (N = 386, α = 0.05). The study explores indicators for six aspects of well-being and happiness, including, good local governance, administrative support for the health system that maintains people’s mental and physical health, environment and weather, job security and a regular income aids them in managing a sustainable lifestyle. The impact of economic security and community relationships on social and cultural capital, and the way these aspects impact on the life style of the community, affects the sustainable well-being of people. Moreover, living with transparency and participatory communication led to diverse rewards in many areas.

Keywords: communication, happiness, well-being, Donkeaw community, social and cultural capital

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Authors: Yu-Chen Chien, Sheng-Jung Ou, Shang-Ling Hsu

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Many aboriginal tribes in the early modern began to actively promote tribal tourism. The tribe uses rich ecological environment and unique folk culture successfully attract crowds. In addition to the tribe in the construction level to consider the cultural heritage and living needs, in order to improve tribal tourism for the tribe to bring the benefits of all levels, as well as to avoid the tourism industry is too prosperous brought negative tourism impact. How to successfully create the conditions of mutual benefit of residents and tourists is an important issue common to many tribes. Hualien Turuku Hongye Tribe in Taiwan around the tourist resources are very rich. It is famous for its Hongye hot springs and Ruisui hot springs. Hongye tribe to develop tribal tourism is bound to use its own has three advantages: Truku culture, in the agricultural products experience and marketing, and the surrounding hot springs industry tourism benefits. Tribal Development Association in the past to promote these three advantages for tribal tourism. But due to the impact of many levels led to the tribes in the promotion of tourism on the ineffective. At present, in addition to the Hongye Tribal Development Association in promoting tribal tourism, local residents to promote cultural heritage workshop also gradually rise. Its purpose is to link local cultural resources, agricultural specialty resources, spa tourism industry, the revitalization of the internal development of the tribes at all levels. Each tribe to promote tribal tourism due to geographical environment, resource types have a different set of practices and patterns. This study explores the tourist opportunities and resource points of Hongye tribes, and tribal tourism has been to promote the operation practices and benefits. To understand the difficulties encountered in the implementation of tribal tourism and the impact of all levels. Reference successful development of domestic and foreign tourism tribal tribe case. Develop a questionnaire and using the questionnaire survey to understand tribal residents for the tribal tribes to promote tribal tourism views. Finally, it puts forward some suggestions and strategies to promote the tribal tourism in Hongye tribe.

Keywords: cultural tourism, tourism impact, aboriginal tribe, Hongye Tribe

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Authors: Guler D. Uzel, Andrew G. Parker, Robert L. Mach, Adly Abd-Alla

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Several tsetse fly species (Diptera: Glossinidae) in natural or colonized populations can be infected with the salivary gland hypertrophy virus (SGHV), a circular dsDNA virus (Hytrosaviridae). The virus infection is mainly asymptomatic but, in some species under certain conditions, the infection can produce salivary gland hypertrophy (SGH) symptoms. In the laboratory colonized tsetse, flies with SGH have reduced fertility, which negatively affects colony performance. Therefore, a high prevalence of SGH in insect mass rearing represents a major challenge for tsetse control using the sterile insect technique. The main objective of this study is to analyze the impact of Glossina pallidipes SGHV infection in various tsetse species on mortality and productivity and its impact on the symbiotic bacteria. Hypertropied salivary glands (SG) were collected from G. pallidipes into phosphate buffered saline (PBS) to prepare suspension; 2 µl aliquots were injected into adults of several tsetse species (G. pallidipes (Gp), G. p. gambiensis (Gpg), G. brevipalpis (Gb), G. morsitans morsitans (Gmm), G. morsitans centralis (Gmc) and G. fuscipes (Gf)) and the change in virus and symbiont titers were analyzed using qPCR. The development of SGH in the F1 was detected by dissection 10 days after emergence and virus infection was confirmed by PCR. The impact of virus infection on fly mortality and productivity was recorded. 2 µl aliquots were also injected into 3rd instar larvae of the different species and the adult SGs assayed by PCR for virus. Virus positive SGs from each species were homogenized in PBS and pooled within species for injection into larvae of the same species. Flies injected with PBS were used as control. Injecting teneral flies with SGHV caused increasing virus titer over time in all species but no SGH was detected. Dissection of the F1 also showed no development of SGH except in Gp (the homologous host). Injection of SGHV did not have any impact on the prevalence of the tsetse symbionts, but an increase in Sodalis titer was observed correlated with fly age regardless of virus infection. The virus infection had a negative impact on productivity and mortality. SGHV injection into larvae of the different species produced SGHV infected glands in the adults determined by PCR with a rate of 60%, 27%, 16%, 7% and 7% for Gp, Gf, Gpg, Gmm and Gmc, respectively. Virus positive SGs observed in the heterologous species were smaller than SGH found in Gp. No virus positive SG was detected by PCR in Gb and no SGH was observed in any adults except in Gp. Injecting virus suspension from the virus positive SGs into conspecific larvae did not produce any adults with infected SGs (except in Gp). SGHV can infect all tested tsetse species. Although the virus can infect and increase in titer in other tsetse species and affect fly mortality and productivity, no vertical virus transmission was observed in other tsetse species with might indicate a transmission barrier in these species, and virus collected from flies injected as larvae was not infective by injection.

Keywords: DNA viruses, glossina, hytrosaviridae, symbiotic bacteria, tsetse

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Authors: C. J. Coetzee, E. Horn

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One of the main challenges in using the Discrete Element Method (DEM) is to specify the correct input parameter values. In general, the models are sensitive to the input parameter values and accurate results can only be achieved if the correct values are specified. For the linear contact model, micro-parameters such as the particle density, stiffness, coefficient of friction, as well as the particle size and shape distributions are required. There is a need for a procedure to accurately calibrate these parameters before any attempt can be made to accurately model a complete bulk materials handling system. Since DEM is often used to model applications in the mining and quarrying industries, a calibration procedure was developed for materials that consist of relatively large (up to 40 mm in size) particles. A coarse crushed aggregate was used as the test material. Using a specially designed large shear box with a diameter of 590 mm, the confined Young’s modulus (bulk stiffness) and internal friction angle of the material were measured by means of the confined compression test and the direct shear test respectively. DEM models of the experimental setup were developed and the input parameter values were varied iteratively until a close correlation between the experimental and numerical results was achieved. The calibration process was validated by modelling the pull-out of an anchor from a bed of material. The model results compared well with experimental measurement.

Keywords: Discrete Element Method (DEM), calibration, shear box, anchor pull-out

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Authors: Samira Ghasempourkazemi

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In terms of the COVID-19 pandemic, lots of mutations in the urban system, which have systemic impacts, have clearly appeared. COVID-19 not only had a direct impact on health but also caused significant losses to other departments, including the economy, education, tourism, environment and the construction industry. Therefore, the pandemic caused a disruption in the whole urban system. Particularly, today’s large urban areas are not designed in order to be compatible during a pandemic. Hence, cities are more vulnerable to infectious disease threats according to the population density, built environment and socioeconomic aspects. Considering the direct relationship between population and rate of infection, higher rates are given to those individuals located in areas with high-density populations. Population density can be a factor that seems to have a strong impact on the spread of infectious diseases. Thus, the preliminary hypothesis can be related to a densely populated areas which become hotspots for the rapid spread of the pandemic due to high levels of interaction. In addition, some other indicators can be effective in this condition, such as age range, education and socio-economy. To figure out the measure of infectious disease risk in densely populated areas in Istanbul is an objective of this study. Besides, this study intends to figure out Vulnerability Index in the case of COVID-19. In order to achieve the proper result, the considered method can be Analytic Hierarchy Process (AHP) by involving the mentioned variables. In the end, the study represents the COVID Vulnerability of densely populated areas in a metro city and the gaps that need to be identified and plugged for the pandemic-resilience city of tomorrow.

Keywords: infectious disease, COVID-19, urban system, densely populated area

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Authors: Stewart A. Keir, Faik A. Hamad

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This study aims to use both analytical and experimental methods of analysis to examine the accuracy of Computational Fluid Dynamics (CFD) models that can then be used for more complex analyses, accurately representing more elaborate flow phenomena such as internal shockwaves and boundary layers. The geometry used in the analytical study and CFD model is taken from the experimental rig. The analytical study is undertaken using isentropic and adiabatic relationships and the output of the analytical study, the 'shockwave location tool', is created. The results from the analytical study are then used to optimize the redesign an experimental rig for more favorable placement of pressure taps and gain a much better representation of the shockwaves occurring in the divergent section of the nozzle. The CFD model is then optimized through the selection of different parameters, e.g. turbulence models (Spalart-Almaras, Realizable k-epsilon & Standard k-omega) in order to develop an accurate, robust model. The results from the CFD model can then be directly compared to experimental and analytical results in order to gauge the accuracy of each method of analysis. The CFD model will be used to visualize the variation of various parameters such as velocity/Mach number, pressure and turbulence across the shock. The CFD results will be used to investigate the interaction between the shock wave and the boundary layer. The validated model can then be used to modify the nozzle designs which may offer better performance and ease of manufacture and may present feasible improvements to existing high-speed flow applications.

Keywords: CFD, nozzle, fluent, gas dynamics, shock-wave

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Authors: Khaleel Alyahya, Faizah Alotaibi

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The coronavirus disease 19 (COVID-19) pandemic has caused an increase in general fear and anxiety around the globe. With the public health measures, including lockdown and travel restrictions, the COVID-19 period further resulted in a sudden increase in the vulnerability of people too ill mental health. This becomes greater among individuals who have a history of mental illness or are undergoing treatment and do not have easy access to medication and medical consultations. The study aims to measure the impact of COVID-19 and the degree of distress with the DASS scale on the mental health of residents living in Saudi Arabia. The study is a quantitative, observational, and cross-sectional conducted in Saudi Arabia to measure the impact of COVID-19 on the mental health of both citizens and residents of Saudi Arabia during pandemics. The study ran from February 2021 to June 2021, and a validated questionnaire was used. The targeted population of the study was Saudi citizens and non-Saudi residents. A sample size of 800 participants was calculated with a single proportion formula at 95% level of significance and 5% allowable error. The result revealed that participants who were always doing exercise experienced the lowest level of depression, anxiety, and stress. The highest prevalence of severe and extremely severe depression was among participants who sometimes do exercise at 53.2% for each. Similar results were obtained for anxiety and stress, where the extremely severe form was reported by those who sometimes did exercise at 54.8% and 72.2%, respectively. There was an inverse association between physical activity levels and levels of depression, anxiety, and stress during the COVID-19. Similarly, the levels of depression, anxiety, and stress differed significantly according to the exercise frequency during COVID-19.

Keywords: mental, COVID-19, pandemic, lockdown, depression, anxiety, stress

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Authors: Anna Lytvynova

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This essay presents labour as a performatively national phenomenon from a cultural perspective. Considering Engels’ proposition of labour as the epicentre of development of social structures and communities, it theorizes the formation and sustainment of group identities through labour identities. Taking labour in the cultural sector as the starting point case study, the essay further enunciates such labour and labour identity as a form of engaged citizenship. In doing so, this piece hopes to arrive at a potential contemporary understanding of labour as having a central and dynamic role in cultural organization and citizenship. A parallel goal is to de-link sociological models of cultural labor from narratives of art and culture as something that stands separate from the 'real world' and the economy and exists in precarity. Combining discourse from cultural sociology, performance studies, and economics and grounding it in historical archive, the essay makes a primarily discursive theoretical contribution. Taking North American theatre organizations as the exemplifying starting point, this project positions cultural workers not solely as workers in a professional industry but as active citizen-subjects who are deeply involved in their society’s democratic processes. The resulting discourse can be used to shape more effective labour policies, as well as help art and cultural organizations find more effective organizational structures to engage the arts in the economic, political, and social spheres.

Keywords: arts labour, cultural sociology, national identity, performativity

Procedia PDF Downloads 127

Authors: Ahmad Saadiq, Neeraj Sahu

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Sediment, which comprises of solid particles of mineral and organic material are transported by water. In river systems, the amount of sediment transported is controlled by both the transport capacity of the flow and the supply of sediment. The transport of sediment in rivers is important with respect to pollution, channel navigability, reservoir ageing, hydroelectric equipment longevity, fish habitat, river aesthetics and scientific interests. The sediment load transported in a river is a very complex hydrological phenomenon. Hence, sediment transport has attracted the attention of engineers from various aspects, and different methods have been used for its estimation. So, several experimental equations have been submitted by experts. Though the results of these methods have considerable differences with each other and with experimental observations, because the sediment measures have some limits, these equations can be used in estimating sediment load. In this present study, two black box models namely, an SRC (Sediment Rating Curve) and ANN (Artificial Neural Network) are used in the simulation of the suspended sediment load. The study is carried out for Seonath subbasin. Seonath is the biggest tributary of Mahanadi river, and it carries a vast amount of sediment. The data is collected for Jondhra hydrological observation station from India-WRIS (Water Resources Information System) and IMD (Indian Meteorological Department). These data include the discharge, sediment concentration and rainfall for 10 years. In this study, sediment load is estimated from the input parameters (discharge, rainfall, and past sediment) in various combination of simulations. A sediment rating curve used the water discharge to estimate the sediment concentration. This estimated sediment concentration is converted to sediment load. Likewise, for the application of these data in ANN, they are normalised first and then fed in various combinations to yield the sediment load. RMSE (root mean square error) and R² (coefficient of determination) between the observed load and the estimated load are used as evaluating criteria. For an ideal model, RMSE is zero and R² is 1. However, as the models used in this study are black box models, they don’t carry the exact representation of the factors which causes sedimentation. Hence, a model which gives the lowest RMSE and highest R² is the best model in this study. The lowest values of RMSE (based on normalised data) for sediment rating curve, feed forward back propagation, cascade forward back propagation and neural network fitting are 0.043425, 0.00679781, 0.0050089 and 0.0043727 respectively. The corresponding values of R² are 0.8258, 0.9941, 0.9968 and 0.9976. This implies that a neural network fitting model is superior to the other models used in this study. However, a drawback of neural network fitting is that it produces few negative estimates, which is not at all tolerable in the field of estimation of sediment load, and hence this model can’t be crowned as the best model among others, based on this study. A cascade forward back propagation produces results much closer to a neural network model and hence this model is the best model based on the present study.

Keywords: artificial neural network, Root mean squared error, sediment, sediment rating curve

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Authors: Chandra Upadhyaya, Arup Kumar Sarma

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In the North Eastern part of India several hydro power projects are being proposed and execution for some of them are already initiated. There are controversies surrounding these constructions. Impact of these dams in the downstream part of the rivers needs to be assessed so that eco-system and people living downstream are protected by redesigning the projects if it becomes necessary. This may result in reducing the stresses to the affected ecosystem and people living downstream. At present many index based ecological methods are present to assess impact on ecology. However, none of these methods are capable of assessing the affect resulting from dam induced diurnal variation of flow in the downstream. We need environmental flow methodology based on hydrological index which can address the affect resulting from dam induced diurnal variation of flow and play an important role in a riverine ecosystem management and be able to provide a qualitative idea about changes in the habitat for aquatic and riparian species.

Keywords: ecosystem, environmental flow assessment, entropy, IHA, TNC

Procedia PDF Downloads 384

Authors: Ejaz Ali, Muhammad Younas, Tahir Saeed

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In this age of information technology, organizations are revisiting their approach in great deal. E-administration is the most popular area to proceed with. Organizations in order to excel over their competitors are spending a substantial chunk of its resources on E-Administration as it is the most effective, transparent and efficient way to achieve their short term as well as long term organizational goals. E-administration being a tool of ICT plays a significant role towards effective management of HR practices resulting into optimal performance of an organization. The present research was carried out to analyze the impact of moderating role of e-administration in the relationships training and performance appraisal aligned with perceived organizational performance. The study is based on RBV and AMO theories, advocating that use of latest technology in execution of human resource (HR) functions enables an organization to achieve and sustain competitive advantage which leads to optimal firm performance.

Keywords: e-administration, human resource management, ict, performance appraisal, training

Procedia PDF Downloads 267