Search results for: mixed effects models

Authors: Zhuoneng Li, Zeeshan A. Rana, Karl W. Jenkins

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In industry, to validate a case, often a multitude of simulation are required and in order to demonstrate confidence in the process where users tend to use a coarser mesh. Therefore, it is imperative to establish the coarsest mesh that could be used while keeping reasonable simulation accuracy. To date, the two most reliable, affordable and broadly used advanced simulations are the hybrid RANS (Reynolds Averaged Navier Stokes)/LES (Large Eddy Simulation) and wall modelled LES. The potentials in these two simulations will still be developed in the next decades mainly because the unaffordable computational cost of a DNS (Direct Numerical Simulation). In the wall modelled LES, the turbulence model is applied as a sub-grid scale model in the most inner layer near the wall. The RANS turbulence models cover the entire boundary layer region in a hybrid RANS/LES (Detached Eddy Simulation) and its variants, therefore, the RANS still has a very important role in the state of art simulations. This research focuses on the turbulence model mesh sensitivity analysis where various turbulence models such as the S-A (Spalart-Allmaras), SSG (Speziale-Sarkar-Gatski), K-Omega transitional SST (Shear Stress Transport), K-kl-Omega, γ-Reθ transitional model, v2f are evaluated within the OpenFOAM. The simulations are conducted on a fully developed turbulent flow over a flat plate where the skin friction coefficient as well as velocity profiles are obtained to compare against experimental values and DNS results. A concrete conclusion is made to clarify the mesh sensitivity for different turbulence models.

Keywords: mesh sensitivity, turbulence models, OpenFOAM, RANS

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Authors: Niya Chen, Jennifer Chan

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In the financial market, risk management helps to minimize potential loss and maximize profit. There are two ways to assess risks; the first way is to calculate the risk directly based on the volatility. The most common risk measurements are Value at Risk (VaR), sharp ratio, and beta. Alternatively, we could look at the quantile of the return to assess the risk. Popular return models such as GARCH and stochastic volatility (SV) focus on modeling the mean of the return distribution via capturing the volatility dynamics; however, the quantile/expectile method will give us an idea of the distribution with the extreme return value. It will allow us to forecast VaR using return which is direct information. The advantage of using these non-parametric methods is that it is not bounded by the distribution assumptions from the parametric method. But the difference between them is that expectile uses a second-order loss function while quantile regression uses a first-order loss function. We consider several quantile functions, different volatility measures, and estimates from some volatility models. To estimate the expectile of the model, we use Realized Conditional Autoregressive Expectile (CARE) model with the bayesian method to achieve this. We would like to see if our proposed models outperform existing models in cryptocurrency, and we will test it by using Bitcoin mainly as well as Ethereum.

Keywords: expectile, CARE Model, CARR Model, quantile, cryptocurrency, Value at Risk

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Authors: Manju, Praveen Aggarwal

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Clayey soil is considered weakest subgrade soil from civil engineering point of view under moist condition. These swelling soils attract and absorb water and losses their strength. Certain inherent properties of these clayey soils need modification for their bulk use in the construction of highways/runways pavements and embankments, etc. In this paper, results of clayey subgrade modified with cement stabilizer is presented. Investigation includes evaluation of specific gravity, Atterberg’s limits, grain size distribution, maximum dry density, optimum moisture content and CBR value of the clayey soil and cement treated clayey soil. A series of proctor compaction and CBR tests (un-soaked and soaked) are carried out on clayey soil and clayey soil mixed with cement stabilizer in 2%, 4% & 6% percentages to the dry weight of soil. In CBR test, under soaked condition best results are obtained with 6% of cement. However, the difference between the CBR value by addition of 4% and 6% cement is not much. Therefore from economical consideration addition of 4% cement gives the best result after soaking period of 90 days.

Keywords: clayey soil, cement, maximum dry density, optimum moisture content, California bearing ratio

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Authors: Luana Parisi, Sohrab Donyavi

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Cities have become the nodes of global networks, standing at the intersection points of the flows of capital, goods, workers, businesses and travellers, making them the spots where innovation, progress and economic development occur. The primary challenge for them is to create the most fertile ecosystems for triggering innovation activities. Design emerges as an essential feature in this process of laboratorisation of cities. This paper aims at exploring the spatial hubs of transformation within the knowledge economy, providing an overview of the current models of innovation spaces, before focusing on the innovation district of one of the cities that are riding the innovation wave, namely, Boston, USA. Useful lessons will be drawn from the case study of the innovation district in Boston, allowing to define precious tools for policymakers, in the form of a range of factors that define the broad strategy able to implement the model successfully. A mixed methodology is implemented, including information from observations, exploratory interviews to key stakeholders and on-desk data.

Keywords: Innovation District, innovation ecosystem, economic development, urban regeneration

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Authors: Emma Van Schie

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The purpose of this study is to use mixed methods research to create typologies of the performance of firms in the cotton-to-clothing value chain in Zimbabwe, and to use these typologies to achieve the objective of adding to the small pool of studies on Sub-Saharan African value chains performing in the context of economic liberalisation and achieving development. The uptake of economic liberalisation measures across Sub-Saharan Africa has led to the restructuring of many value chains. While this action has resulted in some African economies positively reintegrating into global commodity chains, it has also been deeply problematic for the development impacts of the majority of others. Over and above this, these nations have been placed at a disadvantage due to the fact that there is little scholarly and policy research on approaches for managing economic liberalisation and value chain development in the unique African context. As such, the central question facing these less successful cases is how they can integrate into the world economy whilst still fostering their development. This paper draws from quantitative questionnaires and qualitative interviews with 28 stakeholders in the cotton-to-clothing value chain in Zimbabwe. This paper examines the performance of firms in the value chain, and the subsequent local socio-economic development impacts that are affected by the revival of the cotton-to-clothing value chain following its collapse in the wake of Zimbabwe’s uptake of economic liberalisation measures. Firstly, the paper finds the relatively undocumented characteristics and structures of firms in the value chain in the post-economic liberalisation era. As well as this, it finds typologies of the status of firms as either being in operation, closed down, or being placed under judicial management and the common characteristics that these typologies hold. The key findings show how a mixture of macro and local level aspects, such as value chain governance and the management structure of a business, leads to the most successful typology that is able to add value to the chain in the context of economic liberalisation, and thus unlock its socioeconomic development potential. These typologies are used in making industry and policy recommendations on achieving this balance between the macro and the local level, as well as recommendations for further academic research for more typologies and models on the case of cotton value chains in Sub-Saharan Africa. In doing so, this study adds to the small collection of academic evidence and policy recommendations for the challenges that African nations face when trying to incorporate into global commodity chains in attempts to benefit from their associated socioeconomic development opportunities.

Keywords: cotton-to-clothing value chain, economic liberalisation, restructuring value chain, typologies of firms, value chain governance, Zimbabwe

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Authors: Joyce Fernandez

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This study examined the effects of critical incident stress debriefing and other related interventions on the psychological recovery of earthquake survivors. It is a mixed experimental and qualitative study using post-test only control group design and focus group discussion. After the conduct of critical incident stress debriefing activities and other related interventions in the form of counseling and psychiatric treatment to the survivors of a 6.9 magnitude earthquake, a post-test measuring the level of psychological recovery was given to randomized participants categorized as intervention and control groups. Using the traumatic assessment and belief scale as instrument for the quantitative aspect in order to gauge recovery in the psychological need areas of safety, trust, esteem, intimacy and control, the findings are the following: Intervention group participants have relatively better adjustment along the five psychological need areas compared to the control group participants; there is no significant difference in the psychological recovery among female and male participants of the invention and control groups and; there are significant differences between intervention and control groups in the psychological need areas of self-safety, self-trust, other-trust, self-esteem, and self-intimacy. Using a guided interview for the qualitative data, the themes derived are the following. Safety: The world is an unsafe place to live because of the calamities. Trust: Trust and dependence are anchored on the family. Esteem: Participants are having confused self-worth. Intimacy: Participants are thriving on attachment with their family. Control: Participants have unaltered desire to help but feeling restricted because of personal and logistical concerns.As an outcome of the study a Psychosocial Care Program for Individuals, Families and Communities Affected by Disaster and Trauma was proposed.

Keywords: critical incident stress debriefing, earthquake survivors, psychological recovery, related interventions

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Authors: Praveen S. Muthukumarana, Achala C. Aponso

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A large percentage of global crop harvest is lost due to crop diseases. Timely identification and treatment of crop diseases is difficult in many developing nations due to insufficient trained professionals in the field of agriculture. Many crop diseases can be accurately diagnosed by visual symptoms. In the past decade, deep learning has been successfully utilized in domains such as healthcare but adoption in agriculture for plant disease detection is rare. The literature shows that models trained with popular datasets such as PlantVillage does not generalize well on real world images. This paper attempts to find out how to make plant disease identification models that generalize well with real world images.

Keywords: agriculture, convolutional neural network, deep learning, plant disease classification, plant disease detection, plant disease diagnosis

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Authors: Muhammad Khalil, Nader Abuelfoutouh, Gasser Abdelal, Adrian Murphy

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Nowadays, the direct effects of lightning to aircrafts are of great importance because of the massive use of composite materials. In comparison with metallic materials, composites present several weaknesses for lightning strike direct effects. Especially, their low electrical and thermal conductivities lead to severe lightning strike damage. The lightning strike direct effects are burning, heating, magnetic force, sparking and arcing. As the problem is complex, we investigated it gradually. A magnetohydrodynamics (MHD) model is developed to simulate the lightning strikes in order to estimate the damages on the composite materials. Then, a coupled thermal-electrical finite element analysis is used to study the interaction between the lightning arc and the composite laminate and to investigate the material degradation.

Keywords: composite structures, lightning multiphysics, magnetohydrodynamic (MHD), coupled thermal-electrical analysis, thermal plasmas.

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: metaphor detection, deep learning, representation learning, embeddings

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Authors: D. Dixon, J. Nicol, J. A. Coulter, E. Harrison

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The ease with which they can be functionalized, combined with their excellent biocompatibility, make gold nanoparticles (AuNPs) ideal candidates for various applications in nanomedicine. Indeed several promising treatments are currently undergoing human clinical trials (CYT-6091 and Auroshell). A successful nanoparticle treatment must first evade the immune system, then accumulate within the target tissue, before enter the diseased cells and delivering the payload. In order to create a clinically relevant drug delivery system, contrast agent or radiosensitizer, it is generally necessary to functionalize the AuNP surface with multiple groups; e.g. Polyethylene Glycol (PEG) for enhanced stability, targeting groups such as antibodies, peptides for enhanced internalization, and therapeutic agents. Creating and characterizing the biological response of such complex systems remains a challenge. The two commonly used methods to attach multiple groups to the surface of AuNPs are the creation of a mixed monolayer, or by binding groups to the AuNP surface using a bi-functional PEG linker. While some excellent in-vitro and animal results have been reported for both approaches further work is necessary to directly compare the two methods. In this study AuNPs capped with both PEG and a Receptor Mediated Endocytosis (RME) peptide were prepared using both mixed monolayer and PEG linker approaches. The PEG linker used was SH-PEG-SGA which has a thiol at one end for AuNP attachment, and an NHS ester at the other to bind to the peptide. The work builds upon previous studies carried out at the University of Ulster which have investigated AuNP synthesis, the influence of PEG on stability in a range of media and investigated intracellular payload release. 18-19nm citrate capped AuNPs were prepared using the Turkevich method via the sodium citrate reduction of boiling 0.01wt% Chloroauric acid. To produce PEG capped AuNPs, the required amount of PEG-SH (5000Mw) or SH-PEG-SGA (3000Mw Jenkem Technologies) was added, and the solution stirred overnight at room temperature. The RME (sequence: CKKKKKKSEDEYPYVPN, Biomatik) co-functionalised samples were prepared by adding the required amount of peptide to the PEG capped samples and stirring overnight. The appropriate amounts of PEG-SH and RME peptide were added to the AuNP to produce a mixed monolayer consisting of approximately 50% PEG and 50% RME. The PEG linker samples were first fully capped with bi-functional PEG before being capped with RME peptide. An increase in diameter from 18-19mm for the ‘as synthesized’ AuNPs to 40-42nm after PEG capping was observed via DLS. The presence of PEG and RME peptide on both the mixed monolayer and PEG linker co-functionalized samples was confirmed by both FTIR and TGA. Bi-functional PEG linkers allow the entire AuNP surface to be capped with PEG, enabling in-vitro stability to be achieved using a lower molecular weight PEG. The approach also allows the entire outer surface to be coated with peptide or other biologically active groups, whilst also offering the promise of enhanced biological availability. The effect of mixed monolayer versus PEG linker attachment on both stability and non-specific protein corona interactions was also studied.

Keywords: nanomedicine, gold nanoparticles, PEG, biocompatibility

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Authors: Adil Kaval, Digdem Muge Siyez

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With the negative effects of internet use in a person's life, the use of the Internet has become an issue. This subject was mostly considered as internet addiction, and it was investigated. In literature, it is noteworthy that some theoretical models have been proposed to explain the reasons for internet addiction. In addition to these theoretical models, it may be thought that the coping style for stressing events can be a predictor of internet addiction. It was aimed to test with logistic regression the effect of high school students' coping styles on internet addiction levels. Sample of the study consisted of 770 Turkish adolescents (471 girls, 299 boys) selected from high schools in the 2017-2018 academic year in İzmir province. Internet Addiction Test, Coping Scale for Child and Adolescents and a demographic information form were used in this study. The results of the logistic regression analysis indicated that the model of coping styles predicted internet addiction provides a statistically significant prediction of internet addiction. Gender does not predict whether or not to be addicted to the internet. The active coping style is not effective on internet addiction levels, while the avoiding and negative coping style are effective on internet addiction levels. With this model, % 79.1 of internet addiction in high school is estimated. The Negelkerke pseudo R2 indicated that the model accounted for %35 of the total variance. The results of this study on Turkish adolescents are similar to the results of other studies in the literature. It can be argued that avoiding and negative coping styles are important risk factors in the development of internet addiction.

Keywords: adolescents, coping, internet addiction, regression analysis

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305.

Keywords: chemometrics, classification analysis, molecular descriptors, pesticides, regression analysis

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Authors: Selvakumar Ulaganathan, Ivo Couckuyt, Francesco Ferranti, Tom Dhaene, Eric Laermans

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Variable-fidelity surrogate modelling offers an efficient way to approximate function data available in multiple degrees of accuracy each with varying computational cost. In this paper, a Kriging-based variable-fidelity surrogate modelling approach is introduced to approximate such deterministic data. Initially, individual Kriging surrogate models, which are enhanced with gradient data of different degrees of accuracy, are constructed. Then these Gradient enhanced Kriging surrogate models are strategically coupled using a recursive CoKriging formulation to provide an accurate surrogate model for the highest fidelity data. While, intuitively, gradient data is useful to enhance the accuracy of surrogate models, the primary motivation behind this work is to investigate if it is also worthwhile incorporating gradient data of varying degrees of accuracy.

Keywords: Kriging, CoKriging, Surrogate modelling, Variable- fidelity modelling, Gradients

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Authors: Donglan Zha, Jiansong Si

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Because of its flexibility, CES attracts much interest in economic growth and programming models, and the macroeconomics or micro-macro models. This paper focuses on the development, estimating methods of CES production function considering energy as an input. We leave for future research work of relaxing the assumption of constant returns to scale, the introduction of potential input factors, and the generalization method of the optimal nested form of multi-factor production functions.

Keywords: bias of technical change, CES production function, elasticity of substitution, energy input

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Authors: Puttharapong Sakulwaropas, Uraiwan Jaroengeratikun

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Casualty insurance business, the optimal premium pricing and adequate cost for an insurance company are important in risk management. Normally, the insurance pure premium can be determined by multiplying the claim frequency with the claim cost. The aim of this research was to study in the application of generalized linear models to select the risk factor for model of claim frequency and claim cost for estimating a pure premium. In this study, the data set was the claim of comprehensive motor insurance, which was provided by one of the insurance company in Thailand. The results of this study found that the risk factors significantly related to pure premium at the 0.05 level consisted of no claim bonus (NCB) and used of the car (Car code).

Keywords: generalized linear models, risk factor, pure premium, regression model

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Authors: Rebecca J. Hafner, Daniel Read, David Elmes

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The current research applies decision making theory in order to address the problem of increasing uptake of energy-efficient technologies in the market place, where uptake is currently slower than one might predict following rational choice models. Specifically, in two studies we apply the alignable/non-alignable features effect and explore the impact of varying information structure on the consumers’ preference for standard versus energy efficient technologies. As researchers in the Interdisciplinary centre for Storage, Transformation and Upgrading of Thermal Energy (i-STUTE) are currently developing energy efficient heating systems for homes and businesses, we focus on the context of home heating choice, and compare preference for a standard condensing boiler versus an energy efficient heat pump, according to experimental manipulations in the structure of prior information. In Study 1, we find that people prefer stronger alignable features when options are similar; an effect which is mediated by an increased tendency to infer missing information is the same. Yet, in contrast to previous research, we find no effects of alignability on option preference when options differ. The advanced methodological approach used here, which is the first study of its kind to randomly allocate features as either alignable or non-alignable, highlights potential design effects in previous work. Study 2 is designed to explore the interaction between alignability and construal level as an explanation for the shift in attentional focus when options differ. Theoretical and applied implications for promoting energy efficient technologies are discussed.

Keywords: energy-efficient technologies, decision-making, alignability effects, construal level theory, CO2 reduction

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Authors: Edlira Kalemi, Sule Yildirim-Yayilgan

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Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.

Keywords: criminal digital evidence, social media, ontologies, reasoning

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Authors: Hassan Jebreen

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These models of a conservative pollutant in groundwater do not include representation of processes in soils and in the unsaturated zone, or biogeochemical processes in groundwater, These demonstration models can be used as the basis for more detailed simulations of the impacts of pollution sources at a local scale, but such studies should address processes related to specific pollutant species, and should consider local hydrogeology in more detail, particularly in relation to possible impacts on shallow systems which are likely to respond more quickly to changes in pollutant inputs. The results have demonstrated the interaction between groundwater flow fields and pollution sources in abstraction areas, and help to emphasise that wadi development is one of the key elements of water resources planning. The quality of groundwater in the Hebron area indicates a gradual increase in chloride and nitrate with time. Since the aquifers in Hebron districts are highly vulnerable due to their karstic nature, continued disposal of untreated domestic and industrial wastewater into the wadi will lead to unacceptably poor water quality in drinking water, which may ultimately require expensive treatment if significant health problems are to be avoided. Improvements are required in wastewater treatment at the municipal and domestic levels, the latter requiring increased public awareness of the issues, as well as improved understanding of the hydrogeological behaviour of the aquifers.

Keywords: groundwater, models, pollutants, wadis, hebron

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Authors: Said Benkaciali, Mourad Haddadi, Abdallah Khellaf, Kacem Gairaa, Mawloud Guermoui

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In this study, many experiments were carried out to assess the influence of the input parameters on the performance of multilayer perceptron which is one the configuration of the artificial neural networks. To estimate the daily global solar radiation on the horizontal surface, we have developed some models by using seven combinations of twelve meteorological and geographical input parameters collected from a radiometric station installed at Ghardaïa city (southern of Algeria). For selecting of best combination which provides a good accuracy, six statistical formulas (or statistical indicators) have been evaluated, such as the root mean square errors, mean absolute errors, correlation coefficient, and determination coefficient. We noted that multilayer perceptron techniques have the best performance, except when the sunshine duration parameter is not included in the input variables. The maximum of determination coefficient and correlation coefficient are equal to 98.20 and 99.11%. On the other hand, some empirical models were developed to compare their performances with those of multilayer perceptron neural networks. Results obtained show that the neural networks techniques give the best performance compared to the empirical models.

Keywords: empirical models, multilayer perceptron neural network, solar radiation, statistical formulas

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Authors: Azeem Alphonce

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In Pakistan, there is a variety of skin tones and colors across all provinces. However, a fair complexion is one of the standards of beauty among females in Pakistan, which creates insecurities in dark-complexioned females. This research is a critical discourse analysis of the language used on beauty products for females in Pakistan. The purpose was to analyze the language used on female beauty products using Van Dijk's three-stage socio-cognitive model to understand what message is received from the few words written and repeated across the packaging of various facial products, why such language is used and what are its wider socio-cognitive effects? The criterion for the selection of beauty products was skin whitening terminologies and the language used on these products. The results showed that over 57 per cent of products utilized skin-whitening terms. The adjectives written on the package indicate that fairer skin is the ultimate beauty goal of females. The analysis explored how the language reinforces unfair beauty standards and perpetuates colorism. It was concluded that female beauty products utilize discriminatory discourse by marginalizing individuals of darker skin tones. Fairer skin is promoted, whereas darker skin is referred to as a problem, flaw or imperfection. Socially shared mental models seem to have caused beauty companies to exploit and promote perceptions of colorism in society. Therefore, such discourse should be prevented, and beauty companies should utilize their discourse to promote acceptance of various skin tones.

Keywords: language, skin whitening products, beauty standards, social mental models

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Authors: Almudena Konrad, Tomás Galguera

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Lack of motivation and interest is a serious obstacle to students’ learning computing skills. A need exists for a knowledge base on effective pedagogy and curricula to teach computer programming. This paper presents results from research evaluating a six-year project designed to teach complex concepts in computer programming collaboratively, while supporting students to continue developing their computer thinking and related coding skills individually. Utilizing a quasi-experimental, mixed methods design, the pedagogical approaches and methods were assessed in two contrasting groups of students with different socioeconomic status, gender, and age composition. Analyses of quantitative data from Likert-scale surveys and an evaluation rubric, combined with qualitative data from reflective writing exercises and semi-structured interviews yielded convincing evidence of the project’s success at both teaching and inspiring students.

Keywords: computational thinking, computing education, computer programming curriculum, logic, teaching methods

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Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek

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Discrete Choice Experiments (DCE) are used to investigate how product attributes affect decision-makers’ choices. In DCEs, choice situations consisting of several alternatives are presented from which choice-makers select the preferred alternative. Standard multinomial logit models based on random utility theory can be used to estimate the utilities for the attributes. The overarching principle in these models is that respondents understand and use all the attributes when making choices. However, studies suggest that respondents sometimes ignore some attributes (commonly referred to as Attribute Non-Attendance/ANA). The choice modeling literature presents ANA as a static process, i.e., respondents’ ANA behavior does not change throughout the experiment. However, respondents may ignore attributes due to changing factors like availability of information on attributes, learning/fatigue in experiments, etc. We develop a dynamic mixture latent Markov model to model changes in ANA when information on attributes is provided. The model is illustrated on e-consumers’ webshop choices. The results indicate that the dynamic ANA model describes the behavioral changes better than modeling the impact of information using changes in parameters. Further, we find that providing information on attributes leads to an increase in the attendance probabilities for the investigated attributes.

Keywords: choice models, discrete choice experiments, dynamic models, e-commerce, statistical modeling

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Authors: B. Adebayo, A. O. Omotehinse, C. Arum

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This study investigates the suitability of dredged samples for the production of bricks. Some geotechnical properties (moisture content, grain size distribution) of dredged samples were also determined using the British Standard. Bricks were produced using appropriate mixes of two dredged wastes. The dredged samples (Oroto dredged samples and Igbokoda dredged samples) have high moisture content of 90.48 % and 37.5 % respectively and both are classified as silty materials. The two dredged samples were mixed in different percentage (1- Oroto dredged sample (DS) 85 % and Igbokoda dredged sample (IS) 15 %, 2-DS 70 % and IS 30 %, 3- DS 55 % and IS 45 %, 4- DS 50 % and IS 50 %, 5- DS 45 % and IS 55 %,6- DS 30 % and IS 70 %, 7- DS 15 % and IS 85 %, 8- Clay 100 %, 9- DS 100 %, 10-IS 100 %) for the production of bricks and were tested for 7 days, 14 days, 21 days and 28 days. Although, the water absorption level of the bricks produced were high (5.635 to 33.4 %), the compressive strength on the 28th day was within the accepted British Standard. The Igbokoda dredge sample is a good material for the production of bricks when mixed with Oroto Dredged sample because the compressive strength of the material is within the accepted limit.

Keywords: bricks, dredged, moisture content, suitability

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Authors: M. A. Khanday, Aasma Rafiq, Khalid Nazir

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This paper is an attempt to establish the mathematical models to understand the distribution of drug administration in the human body through oral and intravenous routes. Three models were formulated based on diffusion process using Fick’s principle and the law of mass action. The rate constants governing the law of mass action were used on the basis of the drug efficacy at different interfaces. The Laplace transform and eigenvalue methods were used to obtain the solution of the ordinary differential equations concerning the rate of change of concentration in different compartments viz. blood and tissue medium. The drug concentration in the different compartments has been computed using numerical parameters. The results illustrate the variation of drug concentration with respect to time using MATLAB software. It has been observed from the results that the drug concentration decreases in the first compartment and gradually increases in other subsequent compartments.

Keywords: Laplace transform, diffusion, eigenvalue method, mathematical model

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Authors: Roman Klas, František Pochylý, Pavel Rudolf

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This paper is focused on the CFD simulation of the radiaxial pump (i.e. mixed flow pump) with the aim to detect the reasons of Y-Q characteristic instability. The main reasons of pressure pulsations were detected by means of the analysis of velocity and pressure fields within the pump combined with the theoretical approach. Consequently, the modifications of spiral case and pump suction area were made based on the knowledge of flow conditions and the shape of dissipation function. The primary design of pump geometry was created as the base model serving for the comparison of individual modification influences. The basic experimental data are available for this geometry. This approach replaced the more complicated and with respect to convergence of all computational tasks more difficult calculation for the compressible liquid flow. The modification of primary pump consisted in inserting the three fins types. Subsequently, the evaluation of pressure pulsations, specific energy curves and visualization of velocity fields were chosen as the criterion for successful design.

Keywords: CFD, radiaxial pump, spiral case, stability

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Authors: P. Mounnarath, U. Schmitz, Ch. Zhang

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Fragility analysis is an effective tool for the seismic vulnerability assessment of civil structures in the last several years. The design of the expansion joints according to various bridge design codes is almost inconsistent, and only a few studies have focused on this problem so far. In this study, the influence of the expansion joint clearances between the girder ends and the abutment backwalls on the seismic fragility assessment of continuous integral bridge frames is investigated. The gaps (ranging from 60 mm, 150 mm, 250 mm and 350 mm) are designed by following two different bridge design code specifications, namely, Caltrans and Eurocode 8-2. Five bridge models are analyzed and compared. The first bridge model serves as a reference. This model uses three-dimensional reinforced concrete fiber beam-column elements with simplified supports at both ends of the girder. The other four models also employ reinforced concrete fiber beam-column elements but include the abutment backfill stiffness and four different gap values. The nonlinear time history analysis is performed. The artificial ground motion sets, which have the peak ground accelerations (PGAs) ranging from 0.1 g to 1.0 g with an increment of 0.05 g, are taken as input. The soil-structure interaction and the P-Δ effects are also included in the analysis. The component fragility curves in terms of the curvature ductility demand to the capacity ratio of the piers and the displacement demand to the capacity ratio of the abutment sliding bearings are established and compared. The system fragility curves are then obtained by combining the component fragility curves. Our results show that in the component fragility analysis, the reference bridge model exhibits a severe vulnerability compared to that of other sophisticated bridge models for all damage states. In the system fragility analysis, the reference curves illustrate a smaller damage probability in the earlier PGA ranges for the first three damage states, they then show a higher fragility compared to other curves in the larger PGA levels. In the fourth damage state, the reference curve has the smallest vulnerability. In both the component and the system fragility analysis, the same trend is found that the bridge models with smaller clearances exhibit a smaller fragility compared to that with larger openings. However, the bridge model with a maximum clearance still induces a minimum pounding force effect.

Keywords: expansion joint clearance, fiber beam-column element, fragility assessment, time history analysis

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Authors: Yung C. Lin, Kung D. Wu, Wei C. Shih, Jui P. Hung

Abstract:

High speed and high precision machining have become the most important technology in manufacturing industry. The surface roughness of high precision components is regarded as the important characteristics of the product quality. However, machining chatter could damage the machined surface and restricts the process efficiency. Therefore, selection of the appropriate cutting conditions is of importance to prevent the occurrence of chatter. In addition, vibration of the spindle tool also affects the surface quality, which implies the surface precision can be controlled by monitoring the vibration of the spindle tool. Based on this concept, this study was aimed to investigate the influence of the machining conditions on the surface roughness and the vibration of the spindle tool. To this end, a series of machining tests were conducted on aluminum alloy. In tests, the vibration of the spindle tool was measured by using the acceleration sensors. The surface roughness of the machined parts was examined using white light interferometer. The response surface methodology (RSM) was employed to establish the mathematical models for predicting surface finish and tool vibration, respectively. The correlation between the surface roughness and spindle tool vibration was also analyzed by ANOVA analysis. According to the machining tests, machined surface with or without chattering was marked on the lobes diagram as the verification of the machining conditions. Using multivariable regression analysis, the mathematical models for predicting the surface roughness and tool vibrations were developed based on the machining parameters, cutting depth (a), feed rate (f) and spindle speed (s). The predicted roughness is shown to agree well with the measured roughness, an average percentage of errors of 10%. The average percentage of errors of the tool vibrations between the measurements and the predictions of mathematical model is about 7.39%. In addition, the tool vibration under various machining conditions has been found to have a positive influence on the surface roughness (r=0.78). As a conclusion from current results, the mathematical models were successfully developed for the predictions of the surface roughness and vibration level of the spindle tool under different cutting condition, which can help to select appropriate cutting parameters and to monitor the machining conditions to achieve high surface quality in milling operation.

Keywords: machining parameters, machining stability, regression analysis, surface roughness

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Authors: Ghada Mohammed, Mohamed Abdel Salam, Passent Tantawi

Abstract:

The study aimed to investigate the impact of motives and barriers for Egyptian users to use Airbnb as a platform of peer-to-peer accommodation instead of hotels on overall attitude towards Airbnb. A sequential mixed-methods approach was adopted to this study and it proposed a comprehensive research model adapted from both literature and results of qualitative phase and then tested via an online questionnaire. The findings revealed that, motives, price, home benefits, privacy, and online reviews significantly explained overall attitude towards Airbnb, while the main barriers were respectively: perceived risk and distrust in which they can predict the overall attitude. While from the subjective norms, only social influence can predict behavioral intention to use Airbnb. The study may serve as a practical reference for practitioners as well as researchers when developing programs and strategies to manage Airbnb consumers' needs and decision process. Some of the main conclusions drawn from this study are that variety was one of the major things that users like about Airbnb and the most important motives are the functional ones like price rather than the experiential ones like authenticity.

Keywords: airbnb, barriers, disruptive innovation, motives, sharing economy

Procedia PDF Downloads 147

Authors: Vinay Agrawal, Suyash Garg, Ravindra Nagar, Vinay Chandwani

Abstract:

Open ground storey with floating columns is a typical feature in the modern multistory constructions in urban India. Such features are very much undesirable in buildings built in seismically active areas. The present study proposes a feasible solution to mitigate the effects caused due to non-uniformity of stiffness and discontinuity in load path and to simultaneously hold the functional use of the open storey particularly under the floating column, through a combination of various lateral strengthening systems. An investigation is performed on an example building with nine different analytical models to bring out the importance of recognising the presence of open ground storey and floating columns. Two separate analyses on various models of the building namely, the equivalent static analysis and the response spectrum analysis as per IS: 1893-2002 were performed. Various measures such as incorporation of Chevron bracings and shear walls, strengthening the columns in the open ground storey, and their different combinations were examined. The analysis shows that, in comparison to two short ones separated by interconnecting beams, the structural walls are most effective when placed at the periphery of the buildings and used as one long structural wall. Further, it can be shown that the force transfer from floating columns becomes less horizontal when the Chevron Bracings are placed just below them, thereby reducing the shear forces in the beams on which the floating column rests.

Keywords: equivalent static analysis, floating column, open ground storey, response spectrum analysis, shear wall, stiffness irregularity

Procedia PDF Downloads 257

Authors: Omar Qaftan

Abstract:

Earthquakes can cause tremendous loss of human life and can result in severe damage to a several of civil engineering structures especially the tall buildings. The response of a multistory structure subjected to earthquake loading is a complex task, and it requires to be studied by physical and numerical modelling. For many circumstances, the scale models on shaking table may be a more economical option than the similar full-scale tests. A shaking table apparatus is a powerful tool that offers a possibility of understanding the actual behaviour of structural systems under earthquake loading. It is required to use a set of scaling relations to predict the behaviour of the full-scale structure. Selecting the scale factors is the most important steps in the simulation of the prototype into the scaled model. In this paper, the principles of scaling modelling procedure are explained in details, and the simulation of scaled multi-storey concrete structure for dynamic studies is investigated. A procedure for a complete dynamic simulation analysis is investigated experimentally and numerically with a scale factor of 1/50. The frequency domain accounting and lateral displacement for both numerical and experimental scaled models are determined. The procedure allows accounting for the actual dynamic behave of actual size porotype structure and scaled model. The procedure is adapted to determine the effects of the tall multi-storey structure on a raft foundation. Four generated accelerograms were used as inputs for the time history motions which are in complying with EC8. The output results of experimental works expressed regarding displacements and accelerations are compared with those obtained from a conventional fixed-base numerical model. Four-time history was applied in both experimental and numerical models, and they concluded that the experimental has an acceptable output accuracy in compare with the numerical model output. Therefore this modelling methodology is valid and qualified for different shaking table experiments tests.

Keywords: structure, raft, soil, interaction

Procedia PDF Downloads 136