Search results for: hypercholesteraemic mice model
Commenced in January 2007
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Paper Count: 16763

Search results for: hypercholesteraemic mice model

13163 The Magic Bullet in Africa: Exploring an Alternative Theoretical Model

Authors: Daniel Nkrumah

Abstract:

The Magic Bullet theory was a popular media effect theory that defined the power of the mass media in altering beliefs and perceptions of its audiences. However, following the People's Choice study, the theory was said to have been disproved and was supplanted by the Two-Step Flow Theory. This paper examines the relevance of the Magic Bullet theory in Africa and establishes whether it is still relevant in Africa's media spaces and societies. Using selected cases on the continent, it adopts a grounded theory approach and explores a new theoretical model that attempts to enforce an argument that the Two-Step Flow theory though important and valid, was ill-conceived as a direct replacement to the Magic Bullet theory.

Keywords: magic bullet theory, two-step flow theory, media effects, african media

Procedia PDF Downloads 108
13162 Thermodynamic Modeling of Cryogenic Fuel Tanks with a Model-Based Inverse Method

Authors: Pedro A. Marques, Francisco Monteiro, Alessandra Zumbo, Alessia Simonini, Miguel A. Mendez

Abstract:

Cryogenic fuels such as Liquid Hydrogen (LH₂) must be transported and stored at extremely low temperatures. Without expensive active cooling solutions, preventing fuel boil-off over time is impossible. Hence, one must resort to venting systems at the cost of significant energy and fuel mass loss. These losses increase significantly in propellant tanks installed on vehicles, as the presence of external accelerations induces sloshing. Sloshing increases heat and mass transfer rates and leads to significant pressure oscillations, which might further trigger propellant venting. To make LH₂ economically viable, it is essential to minimize these factors by using advanced control techniques. However, these require accurate modelling and a full understanding of the tank's thermodynamics. The present research aims to implement a simple thermodynamic model capable of predicting the state of a cryogenic fuel tank under different operating conditions (i.e., filling, pressurization, fuel extraction, long-term storage, and sloshing). Since this model relies on a set of closure parameters to drive the system's transient response, it must be calibrated using experimental or numerical data. This work focuses on the former approach, wherein the model is calibrated through an experimental campaign carried out on a reduced-scale model of a cryogenic tank. The thermodynamic model of the system is composed of three control volumes: the ullage, the liquid, and the insulating walls. Under this lumped formulation, the governing equations are derived from energy and mass balances in each region, with mass-averaged properties assigned to each of them. The gas-liquid interface is treated as an infinitesimally thin region across which both phases can exchange mass and heat. This results in a coupled system of ordinary differential equations, which must be closed with heat and mass transfer coefficients between each control volume. These parameters are linked to the system evolution via empirical relations derived from different operating regimes of the tank. The derivation of these relations is carried out using an inverse method to find the optimal relations that allow the model to reproduce the available data. This approach extends classic system identification methods beyond linear dynamical systems via a nonlinear optimization step. Thanks to the data-driven assimilation of the closure problem, the resulting model accurately predicts the evolution of the tank's thermodynamics at a negligible computational cost. The lumped model can thus be easily integrated with other submodels to perform complete system simulations in real time. Moreover, by setting the model in a dimensionless form, a scaling analysis allowed us to relate the tested configurations to a representative full-size tank for naval applications. It was thus possible to compare the relative importance of different transport phenomena between the laboratory model and the full-size prototype among the different operating regimes.

Keywords: destratification, hydrogen, modeling, pressure-drop, pressurization, sloshing, thermodynamics

Procedia PDF Downloads 75
13161 Calculation of Effective Masses and Curie Temperature of (Ga, Mn) as Diluted Magnetic Semiconductor from the Eight-band k.p Model

Authors: Khawlh A. Alzubaidi, Khadijah B. Alziyadi, Amor M. Alsayari

Abstract:

The discovery of a dilute magnetic semiconductor (DMS) in which ferromagnetism is carrier-mediated and persists above room temperature is a major step toward the implementation of spintronic devices for processing, transferring, and storing of information. Among the many types of DMS materials which have been investigated, Mn-doped GaAs has become one of the best candidates for technological application. However, despite major developments over the last few decades, the maximum Curie temperature (~200 K) remains well below room temperature. In this work, we have studied the effect of Mn content and strain on the GaMnAs effective masses of electron, heavy and light holes calculated in the different crystallographic direction. Also, the Curie temperature in the DMS GaMnAs alloy is determined. Compilation of GaMnAs band parameters have been carried out using the 8-band k.p model based on Lowdin perturbation theory where spin orbit, sp-d exchange interaction, and biaxial strain are taken into account. Our results show that effective masses, calculated along the different crystallographic directions, have a strong dependence on strain, ranging from -2% (tensile strain) to 2% (compressive strain), and Mn content increased from 1 to 5%. The Curie temperature is determined within the mean-field approach based on the Zener model.

Keywords: diluted magnetic semiconductors, k.p method, effective masses, curie temperature, strain

Procedia PDF Downloads 73
13160 A Three-Dimensional Investigation of Stabilized Turbulent Diffusion Flames Using Different Type of Fuel

Authors: Moataz Medhat, Essam E. Khalil, Hatem Haridy

Abstract:

In the present study, a numerical simulation study is used to 3-D model the steady-state combustion of a staged natural gas flame in a 300 kW swirl-stabilized burner, using ANSYS solver to find the highest combustion efficiency by changing the inlet air swirl number and burner quarl angle in a furnace and showing the effect of flue gas recirculation, type of fuel and staging. The combustion chamber of the gas turbine is a cylinder of diameter 1006.8 mm, and a height of 1651mm ending with a hood until the exhaust cylinder has been reached, where the exit of combustion products which have a diameter of 300 mm, with a height of 751mm. The model was studied by 15 degree of the circumference due to axisymmetric of the geometry and divided into a mesh of about 1.1 million cells. The numerical simulations were performed by solving the governing equations in a three-dimensional model using realizable K-epsilon equations to express the turbulence and non-premixed flamelet combustion model taking into consideration radiation effect. The validation of the results was done by comparing it with other experimental data to ensure the agreement of the results. The study showed two zones of recirculation. The primary one is at the center of the furnace, and the location of the secondary one varies by changing the quarl angle of the burner. It is found that the increase in temperature in the external recirculation zone is a result of increasing the swirl number of the inlet air stream. Also it was found that recirculating part of the combustion products back to the combustion zone decreases pollutants formation especially nitrogen monoxide.

Keywords: burner selection, natural gas, analysis, recirculation

Procedia PDF Downloads 143
13159 Reacting Numerical Simulation of Axisymmetric Trapped Vortex Combustors for Methane, Propane and Hydrogen

Authors: Heval Serhat Uluk, Sam M. Dakka, Kuldeep Singh, Richard Jefferson-Loveday

Abstract:

The carbon footprint of the aviation sector in total measured 3.8% in 2017, and it is expected to triple by 2050. New combustion approaches and fuel types are necessary to prevent this. This paper will focus on using propane, methane, and hydrogen as fuel replacements for kerosene and implement a trapped vortex combustor design to increase efficiency. Reacting simulations were conducted for axisymmetric trapped vortex combustor to investigate the static pressure drop, combustion efficiency and pattern factor for various cavity aspect ratios for 0.3, 0.6 and 1 and air mass flow rates for 14 m/s, 28 m/s and 42 m/s. Propane, methane and hydrogen are used as alternative fuels. The combustion model was anchored based on swirl flame configuration with an emphasis on high fidelity of boundary conditions with favorable results of eddy dissipation model implementation. Reynolds Averaged Navier Stokes (RANS) k-ε model turbulence model for the validation effort was used for turbulence modelling. A grid independence study was conducted for the three-dimensional model to reduce computational time. Preliminary results for 24 m/s air mass flow rate provided a close temperature profile inside the cavity relative to the experimental study. The investigation will be carried out on the effect of air mass flow rates and cavity aspect ratio on the combustion efficiency, pattern factor and static pressure drop in the combustor. A comparison study among pure methane, propane and hydrogen will be conducted to investigate their suitability for trapped vortex combustors and conclude their advantages and disadvantages as a fuel replacement. Therefore, the study will be one of the milestones to achieving 2050 zero carbon emissions or reducing carbon emissions.

Keywords: computational fluid dynamics, aerodynamic, aerospace, propulsion, trapped vortex combustor

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13158 A Bayesian Network Approach to Customer Loyalty Analysis: A Case Study of Home Appliances Industry in Iran

Authors: Azam Abkhiz, Abolghasem Nasir

Abstract:

To achieve sustainable competitive advantage in the market, it is necessary to provide and improve customer satisfaction and Loyalty. To reach this objective, companies need to identify and analyze their customers. Thus, it is critical to measure the level of customer satisfaction and Loyalty very carefully. This study attempts to build a conceptual model to provide clear insights of customer loyalty. Using Bayesian networks (BNs), a model is proposed to evaluate customer loyalty and its consequences, such as repurchase and positive word-of-mouth. BN is a probabilistic approach that predicts the behavior of a system based on observed stochastic events. The most relevant determinants of customer loyalty are identified by the literature review. Perceived value, service quality, trust, corporate image, satisfaction, and switching costs are the most important variables that explain customer loyalty. The data are collected by use of a questionnaire-based survey from 1430 customers of a home appliances manufacturer in Iran. Four scenarios and sensitivity analyses are performed to run and analyze the impact of different determinants on customer loyalty. The proposed model allows businesses to not only set their targets but proactively manage their customer behaviors as well.

Keywords: customer satisfaction, customer loyalty, Bayesian networks, home appliances industry

Procedia PDF Downloads 118
13157 Modeling Flow and Deposition Characteristics of Solid CO2 during Choked Flow of CO2 Pipeline in CCS

Authors: Teng lin, Li Yuxing, Han Hui, Zhao Pengfei, Zhang Datong

Abstract:

With the development of carbon capture and storage (CCS), the flow assurance of CO2 transportation becomes more important, particularly for supercritical CO2 pipelines. The relieving system using the choke valve is applied to control the pressure in CO2 pipeline. However, the temperature of fluid would drop rapidly because of Joule-Thomson cooling (JTC), which may cause solid CO2 form and block the pipe. In this paper, a Computational Fluid Dynamic (CFD) model, using the modified Lagrangian method, Reynold's Stress Transport model (RSM) for turbulence and stochastic tracking model (STM) for particle trajectory, was developed to predict the deposition characteristic of solid carbon dioxide. The model predictions were in good agreement with the experiment data published in the literature. It can be observed that the particle distribution affected the deposition behavior. In the region of the sudden expansion, the smaller particles accumulated tightly on the wall were dominant for pipe blockage. On the contrary, the size of solid CO2 particles deposited near the outlet usually was bigger and the stacked structure was looser. According to the calculation results, the movement of the particles can be regarded as the main four types: turbulent motion close to the sudden expansion structure, balanced motion at sudden expansion-middle region, inertial motion near the outlet and the escape. Furthermore the particle deposits accumulated primarily in the sudden expansion region, reattachment region and outlet region because of the four type of motion. Also the Stokes number had an effect on the deposition ratio and it is recommended for Stokes number to avoid 3-8St.

Keywords: carbon capture and storage, carbon dioxide pipeline, gas-particle flow, deposition

Procedia PDF Downloads 350
13156 Agent-Based Modeling to Simulate the Dynamics of Health Insurance Markets

Authors: Haripriya Chakraborty

Abstract:

The healthcare system in the United States is considered to be one of the most inefficient and expensive systems when compared to other developed countries. Consequently, there are persistent concerns regarding the overall functioning of this system. For instance, the large number of uninsured individuals and high premiums are pressing issues that are shown to have a negative effect on health outcomes with possible life-threatening consequences. The Affordable Care Act (ACA), which was signed into law in 2010, was aimed at improving some of these inefficiencies. This paper aims at providing a computational mechanism to examine some of these inefficiencies and the effects that policy proposals may have on reducing these inefficiencies. Agent-based modeling is an invaluable tool that provides a flexible framework to model complex systems. It can provide an important perspective into the nature of some interactions that occur and how the benefits of these interactions are allocated. In this paper, we propose a novel and versatile agent-based model with realistic assumptions to simulate the dynamics of a health insurance marketplace that contains a mixture of private and public insurers and individuals. We use this model to analyze the characteristics, motivations, payoffs, and strategies of these agents. In addition, we examine the effects of certain policies, including some of the provisions of the ACA, aimed at reducing the uninsured rate and the cost of premiums to move closer to a system that is more equitable and improves health outcomes for the general population. Our test results confirm the usefulness of our agent-based model in studying this complicated issue and suggest some implications for public policies aimed at healthcare reform.

Keywords: agent-based modeling, healthcare reform, insurance markets, public policy

Procedia PDF Downloads 121
13155 Numerical Prediction of Wall Eroded Area by Cavitation

Authors: Ridha Zgolli, Ahmed Belhaj, Maroua Ennouri

Abstract:

This study presents a new method to predict cavitation area that may be eroded. It is based on the post-treatment of URANS simulations in cavitant flows. The most RANS calculations with incompressible consideration are based on cavitation model using mixture fluid with density (ρm) calculated as a function of liquid density (ρliq), vapour or gas density (ρvap) and vapour or gas volume fraction α (ρm = αρvap + (1-α) ρliq). The calculations are performed on hydrofoil geometries and compared with experimental works concerning flows characteristics (size of pocket, pressure, velocity). We present here the used cavitation model and the approach followed to evaluate the value of α fixing the shape of pocket around wall before collapsing.

Keywords: flows, CFD, cavitation, erosion

Procedia PDF Downloads 323
13154 Conceptual Model Providing More Information on the Contact Situation between Crime Victim and the Police

Authors: M. Inzunza

Abstract:

In contemporary society, victims of crime has been given more recognition, which have contributed to advancing the knowledge on the effects of crime. There exists a complexity of who gets the status of victim and that the typology of good versus bad can interfere with the contact situation of the victim with the police. The aim of this study is to identify the most central areas affecting the contact situation between crime victims and the police to develop a conceptual model to be useful empirically. By considering previously documented problem areas and different theoretical domains, a conceptual model has been developed. Preliminary findings suggest that an area that should be given attention is to get a better understanding of the victim, not only in terms of demographics but also in terms of risk behavior and social network. This area has been considered to influence the status of the crime victim. Another domain of value is the type of crime and the context of the incident in more detail. The police officer approach style in the contact situation is also a pertinent area that is influenced by how the police based victim services are organized and how individual police officers are suited for the mission. Suitability includes constructs from empathy models adapted to the police context and especially focusing on sub-constructs such as perspective taking. Discussion will focus on how these findings can be operationalized in practice and how they are used in ongoing empirical studies.

Keywords: empathy, perspective taking, police contact, victim of crime

Procedia PDF Downloads 126
13153 Optimizing Recycling and Reuse Strategies for Circular Construction Materials with Life Cycle Assessment

Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

Abstract:

Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, material recycling, optimization modeling

Procedia PDF Downloads 41
13152 Investigations on the Influence of Optimized Charge Air Cooling for a Diesel Passenger Car

Authors: Christian Doppler, Gernot Hirschl, Gerhard Zsiga

Abstract:

Starting from 2020, an EU-wide CO2-limitation of 95g/km is scheduled for the average of an OEMs passenger car fleet. Considering that, further measures of optimization on the diesel cycle will be necessary in order to reduce fuel consumption and emissions while keeping performance values adequate at the least. The present article deals with charge air cooling (CAC) on the basis of a diesel passenger car model in a 0D/1D-working process calculation environment. The considered engine is a 2.4 litre EURO VI diesel engine with variable geometry turbocharger (VGT) and low-pressure exhaust gas recirculation (LP EGR). The object of study was the impact of charge air cooling on the engine working process at constant boundary conditions which could have been conducted with an available and validated engine model in AVL BOOST. Part load was realized with constant power and NOx-emissions, whereas full load was accomplished with a lambda control in order to obtain maximum engine performance. The informative results were used to implement a simulation model in Matlab/Simulink which is further integrated into a full vehicle simulation environment via coupling with ICOS (Independent Co-Simulation Platform). Next, the dynamic engine behavior was validated and modified with load steps taken from the engine test bed. Due to the modular setup in the Co-Simulation, different CAC-models have been simulated quickly with their different influences on the working process. In doing so, a new cooler variation isn’t needed to be reproduced and implemented into the primary simulation model environment, but is implemented quickly and easily as an independent component into the simulation entity. By means of the association of the engine model, longitudinal dynamics vehicle model and different CAC models (air/air & water/air variants) in both steady state and transient operational modes, statements are gained regarding fuel consumption, NOx-emissions and power behavior. The fact that there is no more need of a complex engine model is very advantageous for the overall simulation volume. Beside of the simulation with the mentioned demonstrator engine, there have also been conducted several experimental investigations on the engine test bench. Here the comparison of a standard CAC with an intake-manifold-integrated CAC was executed in particular. Simulative as well as experimental tests showed benefits for the water/air CAC variant (on test bed especially the intake manifold integrated variant). The benefits are illustrated by a reduced pressure loss and a gain in air efficiency and CAC efficiency, those who all lead to minimized emission and fuel consumption for stationary and transient operation.

Keywords: air/water-charge air cooler, co-simulation, diesel working process, EURO VI fuel consumption

Procedia PDF Downloads 250
13151 Explainable Graph Attention Networks

Authors: David Pham, Yongfeng Zhang

Abstract:

Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

Procedia PDF Downloads 165
13150 Studies on Dye Removal by Aspergillus niger Strain

Authors: M. S. Mahmoud, Samah A. Mohamed, Neama A. Sobhy

Abstract:

For color removal from wastewater containing organic contaminants, biological treatment systems have been widely used such as physical and chemical methods of flocculation, coagulation. Fungal decolorization of dye containing wastewater is one of important goal in industrial wastewater treatment. This work was aimed to characterize Aspergillus niger strain for dye removal from aqueous solution and from raw textile wastewater. Batch experiments were studied for removal of color using fungal isolate biomass under different conditions. Environmental conditions like pH, contact time, adsorbent dose and initial dye concentration were studied. Influence of the pH on the removal of azo dye by Aspergillus niger was carried out between pH 1.0 and pH 11.0. The optimum pH for red dye decolonization was 9.0. Results showed the decolorization of dye was decreased with the increase of its initial dye concentration. The adsorption data was analyzed based on the models of equilibrium isotherm (Freundlich model and Langmuir model). During the adsorption isotherm studies; dye removal was better fitted to Freundlich model. The isolated fungal biomass was characterized according to its surface area both pre and post the decolorization process by Scanning Electron Microscope (SEM) analysis. Results indicate that the isolated fungal biomass showed higher affinity for dye in decolorization process.

Keywords: biomass, biosorption, dye, isotherms

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13149 3D Microbubble Dynamics in a Weakly Viscous Fluid Near a Rigid Boundary Subject to Ultrasound

Authors: K. Manmi, Q. X. Wang

Abstract:

This paper investigates microbubble dynamics subject to ultrasound in a weakly viscous fluid near a rigid boundary. The phenomenon is simulated using a boundary integral method. The weak viscous effects are incorporated into the model through the normal stress balance across the bubble surface. The model agrees well with the Rayleigh-Plesset equation for a spherical bubble for several cycles. The effects of the fluid viscosity in the bubble dynamics are analyzed, including jet development, centroid movement and bubble volume.

Keywords: microbubble dynamics, bubble jetting, viscous effect, boundary integral method

Procedia PDF Downloads 463
13148 Impact of Health Indicators on Economic Growth: Application of Ardl Model on Pakistan’s Data Set

Authors: Sheraz Ahmad Choudhary

Abstract:

Health plays a vital role in the growth. The study examined the effect of health indicator on the growth of Pakistan. ARDL model is used to check the growth rate which is affected by the health by using the time series date of Pakistan from 1990 to 2017. Health indicator, fertility rate, life expectancy, foreign direct investment, and infant mortality rate are variables Where the unit root is applied to check the stationarity of the model. consequences find a significant relationship between GDP, foreign direct investment, fertility rate, and life expectancy in the short run, whereas mortality rate effected negatively to economic growth but have significant values. In the long run, foreign direct investment (FDI) and fertility rate(FR) have significantly influenced the GDP. The results show thateconomic growth is positively stimulated by most of the health indicators. The study accomplishes that nations can achieve a high level of economic growth by increasing wellbeing human capital.

Keywords: economic growth, health expenditures, fertility rate, human capital, life expectancy, foreign direct investment, and infant mortality rate

Procedia PDF Downloads 111
13147 Optimizing Recycling and Reuse Strategies for Circular Construction Materials with Life Cycle Assessment

Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

Abstract:

Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, life cycle assessment, material recycling

Procedia PDF Downloads 56
13146 Development of a Model Based on Wavelets and Matrices for the Treatment of Weakly Singular Partial Integro-Differential Equations

Authors: Somveer Singh, Vineet Kumar Singh

Abstract:

We present a new model based on viscoelasticity for the Non-Newtonian fluids.We use a matrix formulated algorithm to approximate solutions of a class of partial integro-differential equations with the given initial and boundary conditions. Some numerical results are presented to simplify application of operational matrix formulation and reduce the computational cost. Convergence analysis, error estimation and numerical stability of the method are also investigated. Finally, some test examples are given to demonstrate accuracy and efficiency of the proposed method.

Keywords: Legendre Wavelets, operational matrices, partial integro-differential equation, viscoelasticity

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13145 Confidence Envelopes for Parametric Model Selection Inference and Post-Model Selection Inference

Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

Abstract:

In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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13144 Studying the Impact of Agricultural Producers Support Policy in Export Market

Authors: Yazdani Saeed, Rafiei Hamed, Nekoofar Farahnaz

Abstract:

Governments Policies play a major role in national and international Markets. Pistachio is one of the most important non-oil export commodity of Iran. Therefore, in this study the relation between the producer support policies and the export of Pistachio was examined. An econometric model (VAR) was applied to test the study hypothesis. According to the estimated coefficient in VAR model, lag of producer support index has a significant and negative effect on variation of Pistachio’s export in short term. In other word, in short term, export advantage index is dependent on the amount of producers support in previous period.

Keywords: producer support, export advantage, pistachio, Iran

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13143 Theology and Music in the XXI. Century: An Exploratory Study of Current Interrelation

Authors: Andrzej Kesiak

Abstract:

Contemporary theology is often accused of answering questions that nobody is asking, and of employing hermetic language that has lost its communication capacity. There is also a question that theology is asking itself: how theological discourse can still be influential on other disciplines and, how to overcome the separation of theology and belief. Undoubtedly, in the wider spectrum, the theological discourse has been and will be needed. The difficulty is how to find the right model of it, the model that would help theology to enter in dialogue with culture, art, science, and politics. Presumably, there is no only one such model, theology constantly needs to seek such models, and this is probably a never-ending journey; in other words, theology should adopt a profile of ‘a restless being’ if it wants to remain influential. Music, on the other hand, has always been very close to theology; in fact, a huge part of classical music is either sacred or religious. Many composers sought inspiration in religion, liturgy, religious painting and sacred texts. This paper will argue that despite all that it seems that a proper and factual dialogue is still in a starting phase. Such a thing as a reciprocal relationship between theology and music definitely exists, but it has not yet been theoretically developed enough. Correlation between musical and theological disciplines constitutes a very broad and complex discourse. Therefore this study would rather narrow the subject and put it in a specific context: Theology and Music in the XXI. Century. This paper is a text-based study; therefore it will be based on textual-analysis with elements of the text hermeneutics.

Keywords: music, theology, reciprocal relationship between theology and music, XXI Century

Procedia PDF Downloads 142
13142 Spontaneous and Posed Smile Detection: Deep Learning, Traditional Machine Learning, and Human Performance

Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

Abstract:

A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

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13141 The Model Establishment and Analysis of TRACE/FRAPTRAN for Chinshan Nuclear Power Plant Spent Fuel Pool

Authors: J. R. Wang, H. T. Lin, Y. S. Tseng, W. Y. Li, H. C. Chen, S. W. Chen, C. Shih

Abstract:

TRACE is developed by U.S. NRC for the nuclear power plants (NPPs) safety analysis. We focus on the establishment and application of TRACE/FRAPTRAN/SNAP models for Chinshan NPP (BWR/4) spent fuel pool in this research. The geometry is 12.17 m × 7.87 m × 11.61 m for the spent fuel pool. In this study, there are three TRACE/SNAP models: one-channel, two-channel, and multi-channel TRACE/SNAP model. Additionally, the cooling system failure of the spent fuel pool was simulated and analyzed by using the above models. According to the analysis results, the peak cladding temperature response was more accurate in the multi-channel TRACE/SNAP model. The results depicted that the uncovered of the fuels occurred at 2.7 day after the cooling system failed. In order to estimate the detailed fuel rods performance, FRAPTRAN code was used in this research. According to the results of FRAPTRAN, the highest cladding temperature located on the node 21 of the fuel rod (the highest node at node 23) and the cladding burst roughly after 3.7 day.

Keywords: TRACE, FRAPTRAN, BWR, spent fuel pool

Procedia PDF Downloads 336
13140 Audio-Visual Recognition Based on Effective Model and Distillation

Authors: Heng Yang, Tao Luo, Yakun Zhang, Kai Wang, Wei Qin, Liang Xie, Ye Yan, Erwei Yin

Abstract:

Recent years have seen that audio-visual recognition has shown great potential in a strong noise environment. The existing method of audio-visual recognition has explored methods with ResNet and feature fusion. However, on the one hand, ResNet always occupies a large amount of memory resources, restricting the application in engineering. On the other hand, the feature merging also brings some interferences in a high noise environment. In order to solve the problems, we proposed an effective framework with bidirectional distillation. At first, in consideration of the good performance in extracting of features, we chose the light model, Efficientnet as our extractor of spatial features. Secondly, self-distillation was applied to learn more information from raw data. Finally, we proposed a bidirectional distillation in decision-level fusion. In more detail, our experimental results are based on a multi-model dataset from 24 volunteers. Eventually, the lipreading accuracy of our framework was increased by 2.3% compared with existing systems, and our framework made progress in audio-visual fusion in a high noise environment compared with the system of audio recognition without visual.

Keywords: lipreading, audio-visual, Efficientnet, distillation

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13139 SQL Generator Based on MVC Pattern

Authors: Chanchai Supaartagorn

Abstract:

Structured Query Language (SQL) is the standard de facto language to access and manipulate data in a relational database. Although SQL is a language that is simple and powerful, most novice users will have trouble with SQL syntax. Thus, we are presenting SQL generator tool which is capable of translating actions and displaying SQL commands and data sets simultaneously. The tool was developed based on Model-View-Controller (MVC) pattern. The MVC pattern is a widely used software design pattern that enforces the separation between the input, processing, and output of an application. Developers take full advantage of it to reduce the complexity in architectural design and to increase flexibility and reuse of code. In addition, we use White-Box testing for the code verification in the Model module.

Keywords: MVC, relational database, SQL, White-Box testing

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13138 Discrete Tracking Control of Nonholonomic Mobile Robots: Backstepping Design Approach

Authors: Alexander S. Andreev, Olga A. Peregudova

Abstract:

In this paper, we propose a discrete tracking control of nonholonomic mobile robots with two degrees of freedom. The electro-mechanical model of a mobile robot moving on a horizontal surface without slipping, with two rear wheels controlled by two independent DC electric, and one front roal wheel is considered. We present back-stepping design based on the Euler approximate discrete-time model of a continuous-time plant. Theoretical considerations are verified by numerical simulation. The work was supported by RFFI (15-01-08482).

Keywords: actuator dynamics, back stepping, discrete-time controller, Lyapunov function, wheeled mobile robot

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13137 Evaluation of Duncan-Chang Deformation Parameters of Granular Fill Materials Using Non-Invasive Seismic Wave Methods

Authors: Ehsan Pegah, Huabei Liu

Abstract:

Characterizing the deformation properties of fill materials in a wide stress range always has been an important issue in geotechnical engineering. The hyperbolic Duncan-Chang model is a very popular model of stress-strain relationship that captures the nonlinear deformation of granular geomaterials in a very tractable manner. It consists of a particular set of the model parameters, which are generally measured from an extensive series of laboratory triaxial tests. This practice is both time-consuming and costly, especially in large projects. In addition, undesired effects caused by soil disturbance during the sampling procedure also may yield a large degree of uncertainty in the results. Accordingly, non-invasive geophysical seismic approaches may be utilized as the appropriate alternative surveys for measuring the model parameters based on the seismic wave velocities. To this end, the conventional seismic refraction profiles were carried out in the test sites with the granular fill materials to collect the seismic waves information. The acquired shot gathers are processed, from which the P- and S-wave velocities can be derived. The P-wave velocities are extracted from the Seismic Refraction Tomography (SRT) technique while S-wave velocities are obtained by the Multichannel Analysis of Surface Waves (MASW) method. The velocity values were then utilized with the equations resulting from the rigorous theories of elasticity and soil mechanics to evaluate the Duncan-Chang model parameters. The derived parameters were finally compared with those from laboratory tests to validate the reliability of the results. The findings of this study may confidently serve as the useful references for determination of nonlinear deformation parameters of granular fill geomaterials. Those are environmentally friendly and quite economic, which can yield accurate results under the actual in-situ conditions using the surface seismic methods.

Keywords: Duncan-Chang deformation parameters, granular fill materials, seismic waves velocity, multichannel analysis of surface waves, seismic refraction tomography

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13136 Mathematics as the Foundation for the STEM Disciplines: Different Pedagogical Strategies Addressed

Authors: Marion G. Ben-Jacob, David Wang

Abstract:

There is a mathematics requirement for entry level college and university students, especially those who plan to study STEM (Science, Technology, Engineering and Mathematics). Most of them take College Algebra, and to continue their studies, they need to succeed in this course. Different pedagogical strategies are employed to promote the success of our students. There is, of course, the Traditional Method of teaching- lecture, examples, problems for students to solve. The Emporium Model, another pedagogical approach, replaces traditional lectures with a learning resource center model featuring interactive software and on-demand personalized assistance. This presentation will compare these two methods of pedagogy and the study done with its results on this comparison. Math is the foundation for science, technology, and engineering. Its work is generally used in STEM to find patterns in data. These patterns can be used to test relationships, draw general conclusions about data, and model the real world. In STEM, solutions to problems are analyzed, reasoned, and interpreted using math abilities in a assortment of real-world scenarios. This presentation will examine specific examples of how math is used in the different STEM disciplines. Math becomes practical in science when it is used to model natural and artificial experiments to identify a problem and develop a solution for it. As we analyze data, we are using math to find the statistical correlation between the cause of an effect. Scientists who use math include the following: data scientists, scientists, biologists and geologists. Without math, most technology would not be possible. Math is the basis of binary, and without programming, you just have the hardware. Addition, subtraction, multiplication, and division is also used in almost every program written. Mathematical algorithms are inherent in software as well. Mechanical engineers analyze scientific data to design robots by applying math and using the software. Electrical engineers use math to help design and test electrical equipment. They also use math when creating computer simulations and designing new products. Chemical engineers often use mathematics in the lab. Advanced computer software is used to aid in their research and production processes to model theoretical synthesis techniques and properties of chemical compounds. Mathematics mastery is crucial for success in the STEM disciplines. Pedagogical research on formative strategies and necessary topics to be covered are essential.

Keywords: emporium model, mathematics, pedagogy, STEM

Procedia PDF Downloads 54
13135 Scale Effects on the Wake Airflow of a Heavy Truck

Authors: Aude Pérard Lecomte, Georges Fokoua, Amine Mehel, Anne Tanière

Abstract:

Air quality in urban areas is deteriorated by pollution, mainly due to the constant increase of the traffic of different types of ground vehicles. In particular, particulate matter pollution with important concentrations in urban areas can cause serious health issues. Characterizing and understanding particle dynamics is therefore essential to establish recommendations to improve air quality in urban areas. To analyze the effects of turbulence on particulate pollutants dispersion, the first step is to focus on the single-phase flow structure and turbulence characteristics in the wake of a heavy truck model. To achieve this, Computational Fluid Dynamics (CFD) simulations were conducted with the aim of modeling the wake airflow of a full- and reduced-scale heavy truck. The Reynolds Average Navier-Stokes (RANS) approach with the Reynolds Stress Model (RSM)as the turbulence model closure was used. The simulations highlight the apparition of a large vortex coming from the under trailer. This vortex belongs to the recirculation region, located in the near-wake of the heavy truck. These vortical structures are expected to have a strong influence on particle dynamics that are emitted by the truck.

Keywords: CDF, heavy truck, recirculation region, reduced scale

Procedia PDF Downloads 201
13134 Artificial Neural Network and Statistical Method

Authors: Tomas Berhanu Bekele

Abstract:

Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea of avoiding traffic instabilities and homogenizing traffic flow in such a way that the risk of accidents is minimized and traffic flow is maximized. Lately, Intelligent Transport Systems (ITS) has become an important area of research to solve such road traffic-related issues for making smart decisions. It links people, roads and vehicles together using communication technologies to increase safety and mobility. Moreover, accurate prediction of road traffic is important to manage traffic congestion. The aim of this study is to develop an ANN model for the prediction of traffic flow and to compare the ANN model with the linear regression model of traffic flow predictions. Data extraction was carried out in intervals of 15 minutes from the video player. Video of mixed traffic flow was taken and then counted during office work in order to determine the traffic volume. Vehicles were classified into six categories, namely Car, Motorcycle, Minibus, mid-bus, Bus, and Truck vehicles. The average time taken by each vehicle type to travel the trap length was measured by time displayed on a video screen.

Keywords: intelligent transport system (ITS), traffic flow prediction, artificial neural network (ANN), linear regression

Procedia PDF Downloads 44