Search results for: experimental model

Authors: Mahboobeh Mohadeszadeh, Behzad Padidaran Moghaddam

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In order to measuring dinuclear molybdenum complexes formation constant First,the reactants and the products were optimized separately and then, their frequencies were measured. In next level , with using Hartree-fock (HF) and density functional theory (DFT) methods ,Theoretical studies on the geometrical parameters, electronic properties and vibrational frequencies of dinuclear molybdenum complexes [C40H44Mo2N2O20] were investigated . These calculations were performed with the B3LYP, BPV86, B3PW91 and HF theoretical method using the LANL2DZ (for Mo’s) + 6-311G (for others) basis sets. To estimate the error rate between theoretical data and experimental data, RSquare , SError and RMS values that according with the theoretical and experimental parameters found out DFT methods has more integration with experimental data compare to HF methods. In addition, through electron specification of compounds, the percentage of atomic orbital’s attendance in making molecular orbital’s, atoms electrical charge, the sustainable energy resulting and also HOMO and LUMO orbital’s energy achieved.

Keywords: geometrical parameters, hydrogen bonding, electronic properties, vibrational frequencies

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Authors: Omar Al Denali, Abdelaziz Badi

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The ASTM A516 Grade 70 steel is a suitable material used for the fabrication of boiler pressure vessels working in moderate and lower temperature services, and it has good weldability and excellent notch toughness. The post-weld heat treatment (PWHT) or stress-relieving heat treatment has significant effects on avoiding the martensite transformation and resulting in high hardness, which can lead to cracking in the heat-affected zone (HAZ). An adaptive neuro-fuzzy inference system (ANFIS) was implemented to predict the material tensile strength of post-weld heat treatment (PWHT) experiments. The ANFIS models presented excellent predictions, and the comparison was carried out based on the mean absolute percentage error between the predicted values and the experimental values. The ANFIS model gave a Mean Absolute Percentage Error of 0.556 %, which confirms the high accuracy of the model.

Keywords: prediction, post-weld heat treatment, adaptive neuro-fuzzy inference system, mean absolute percentage error

Procedia PDF Downloads 153

Authors: Shahid Mahboob, Hafiz Muhammad Ashraf, Salma Sultana, Tayyaba Sultana, Khalid Al-Ghanim, Fahid Al-Misned, Zubair Ahmedd

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There is an increasing need for an effective tool to estimate the risks derived from the large number of pollutants released to the environment by human activities. Typical screening procedures are highly invasive or lethal to the fish. Recent studies show that fish scales biochemically respond to a range of contaminants, including toxic metals, organic compounds, and endocrine disruptors. The present study evaluated the effects of the surface water contaminants on Cyprinus carpio in the Ravi River by comparing DNA extracted non-lethally from their scales to DNA extracted from the scales of fish collected from a controlled fish farm. A single, random sampling was conducted. Fish were broadly categorised into three weight categories (W1, W2 and W3). The experimental samples in the W1, W2 and W3 categories had an average DNA concentration (µg/µl) that was lower than the control samples. All control samples had a single DNA band; whereas the experimental samples in W1 fish had 1 to 2 bands, the experimental samples in W2 fish had two bands and the experimental samples in W3 fish had fragmentation in the form of three bands. These bands exhibit the effects of pollution on fish in the Ravi River. On the basis findings of this study, we propose that fish scales can be successfully employed as a new non-lethal tool for the evaluation of the effect of surface water contaminants.

Keywords: fish scales, Cyprinus carpio, heavy metals, non-invasive, DNA fragmentation

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Authors: I Putu Indra Kusuma

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The rapid development of Information and Communication Technology (ICT) tools has improved the implementation of flipped classrooms in English Language Teaching (ELT), especially in speaking course. Flipped classrooms have therefore evolved from the oldest version, which uses recorded videos to the newest one (3.0 version), which combines various materials and enables out-of-class interaction and learning engagement. However, how the latest version of flipped classrooms affects students’ speaking performance and influences students’ learning engagement remains unclear. This study therefore sought (1) to examine the effect of flipped classrooms 3.0 towards students’ speaking performance and (2) to explore the students’ learning engagement during the implementation of flipped classrooms in the speaking course. This study then employed explanatory sequential mixed-method design. This study conducted a quasi-experimental study by recruiting 164 twelfth grade students of a public senior high school in Indonesia as the sample. They were distributed into experimental (80 students) and control (84 students) groups. The experimental group was treated by implementing flipped classrooms with various use of ICT tools such as Schoology, Youtube, websites, and Flipgrid for eight weeks. Meanwhile, the control group implemented a conventional method. Furthermore, there were two variables examined in this study, such as the implementation of flipped classrooms 3.0 as the independent variable and students’ speaking performance as the dependent variable. The data of these two variables were then collected through administering a speaking test to both groups. The data from this experimental study were analyzed by using independent t-test analysis. Also, five students were invited to participate in semi-structured interviews to explore their learning engagement during the implementation of flipped classrooms. The findings revealed that there was a significant difference in students’ speaking performance between experimental where t (df = 162) = 5.810, p < 0.001, d = 0.91 in which experimental group performed better in speaking than the control group. Also, the results of interviews showed that the students had positive learning engagement during the implementation of flipped classrooms 3.0, especially on out-of-class interactions and face-to-face meetings. Some relevant implications to ELT, especially in speaking courses, are also drawn from the data findings. From the findings, it can be concluded that flipped classrooms 3.0 has a significant effect on students’ speaking performance and it promotes students’ learning engagement. Therefore, flipped classrooms 3.0 should be embraced as the newest version of flipped classrooms that promotes interaction outside the classrooms and learning engagement.

Keywords: Flipped Classrooms 3.0, learning engagement, teaching speaking with technology, technology-enhanced language learning

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Authors: Yosr Ghozzi

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The Cyber-Physical Systems terminology has been well received by the industrial community and specifically appropriated in educational settings. Indeed, our latest educational activities are based on the development of experimental platforms on an industrial scale. In fact, we built a collaborative learning model because of an international market study that led us to place ourselves at the heart of this technology. To align with these findings, a competency-based approach study was conducted, and program content was revised by reflecting the projectbased approach. Thus, this article deals with the development of educational devices according to a generated curriculum and specific educational activities while respecting the repository of skills adopted from what constitutes the educational cyber-physical production systems and the laboratories that are compliant and adapted to them. The implementation of these platforms was systematically carried out in the school's workshops spaces. The objective has been twofold, both research and teaching for the students in mechatronics and logistics of the electromechanical department. We act as trainers and industrial experts to involve students in the implementation of possible extension systems around multidisciplinary projects and reconnect with industrial projects for better professional integration.

Keywords: education 4.0, competency-based learning, teaching factory, project-based learning, cyber-physical systems, industry 4.0

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Authors: Guillaume Linassier, Morgan Balland, Hugo Pervier, Marie Pervier, David Hammond

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Atmospheric icing for turbojet is caused by ingestion of super-cooled water droplets. To prevent operability risks, manufacturer can implement ice protection systems. Thermal systems are commonly used for this purpose, but their activation can cause the formation of a water liquid film, that can freeze downstream the heated surface or even on other components. In the framework of STORM, a European project dedicated to icing physics in turbojet engines, a cascade rig representative of engine inlet blades was built and tested in an icing wind tunnel. This mock-up integrates two rows of blades, the upstream one being anti-iced using an electro-thermal device the downstream one being unheated. Under icing conditions, the anti-icing system is activated and set at power level to observe a liquid film on the surface and droplet re-emission at the trailing edge. These re-emitted droplets will impinge on the downstream row and contribute to ice accretion. A complete experimental database was generated, including the characterization of ice accretion shapes, and the characterization of electro-thermal anti-icing system (power limit for apparition of the runback water or ice accretion). These data will be used for validation of numerical tools for modeling thermal anti-icing systems in the scope of engine application, as well as validation of re-emission droplets model for stator parts.

Keywords: turbomachine, anti-icing, cascade rig, runback water

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Authors: Robert Setekera, Ramses van der Toorn

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We present an extensive analysis of the temperature dependence of the local avalanche model used in most of the modern compact models for bipolar transistors. This local avalanche model uses the Chynoweth's empirical law for ionization coefficient to define the generation of the avalanche current in terms of the local electric field. We carry out the model analysis using DC-measurements taken on both Si and advanced SiGe bipolar transistors. For the advanced industrial SiGe-HBTs, we consider both high-speed and high-power devices (both NPN and PNP transistors). The limitations of the local avalanche model in modeling the temperature dependence of the avalanche current mostly in the weak avalanche region are demonstrated. In addition, the model avalanche parameters are analyzed to see if they are in agreement with semiconductor device physics.

Keywords: avalanche multiplication, avalanche current, bipolar transistors, compact modeling, electric field, impact ionization, local avalanche

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Authors: Jiri Dufek

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The national model of the Czech Republic has been modified in a detailed way to get detailed travel demand in the municipality level (cities, villages over 300 inhabitants). As a technique for this detailed modelling, three-dimensional procedure for calibrating gravity models, was used. Besides of zone production and attraction, which is usual in gravity models, the next additional parameter for trip distribution was introduced. Usually it is called by “third dimension”. In the model, this parameter is a demand between regions. The distribution procedure involved calculation of appropriate skim matrices and its multiplication by three coefficients obtained by iterative balancing of production, attraction and third dimension. This type of trip distribution was processed in R-project and the results were used in the Czech Republic transport model, created in PTV Vision. This process generated more precise results in local level od the model (towns, villages)

Keywords: trip distribution, three dimension, transport model, municipalities

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Authors: Ksenija Dumičić, Anita Čeh Časni, Berislav Žmuk

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The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which accounts for trend and seasonality. The results of the empirical analysis showed that the optimal model for forecasting unemployment rate in Greece was Holt-Winters` additive method. In the case of Spain, according to MAPE, the optimal model was double exponential smoothing model. Furthermore, for Croatia and Italy the best forecasting model for unemployment rate was Holt-Winters` multiplicative model, whereas in the case of Portugal the best model to forecast unemployment rate was Double exponential smoothing model. Our findings are in line with European Commission unemployment rate estimates.

Keywords: European Union countries, exponential smoothing methods, forecast accuracy unemployment rate

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Authors: Mohsen Solimani Babarsad, Payam Taheri

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Numerical results of vertical slot fishways with and without cylinders study are presented. The simulated results and the measured data in the fishways are compared to validate the application of the model. This investigation is made using FLUENT V.6.3, a Computational Fluid Dynamics solver. Advantages of using these types of numerical tools are the possibility of avoiding the St.-Venant equations’ limitations, and turbulence can be modeled by means of different models such as the k-ε model. In general, the present study has demonstrated that the CFD model could be useful for analysis and design of vertical slot fishways with cylinders.

Keywords: slot Fish-way, CFD, k-ε model, St.-Venant equations’

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Authors: Yooncheol Lee, Jeongmin Kim, Kwang Ryel Ryu

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This paper deals with the establishment of a short-term operational plan for an air conditioner for efficient energy management of exhibition hall. The short-term operational plan is composed of a time series of operational schedules, which we have searched using genetic algorithms. Establishing operational schedule should be considered the future trends of the variables affecting the exhibition hall environment. To reflect continuously changing factors such as external temperature and occupant, short-term operational plans should be updated in real time. But it takes too much time to evaluate a short-term operational plan using EnergyPlus, a building emulation tool. For that reason, it is difficult to update the operational plan in real time. To evaluate the short-term operational plan, we designed prediction models based on machine learning with fast evaluation speed. This model, which was created by learning the past operational data, is accurate and fast. The collection of operational data and the verification of operational plans were made using EnergyPlus. Experimental results show that the proposed method can save energy compared to the reactive control method.

Keywords: exhibition hall, energy management, predictive model, simulation-based optimization

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Authors: Ilham Ihoume, Rachid Tadili, Nora Arbaoui

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One of the most crucial ways to combat food insecurity is to minimize crop losses; food drying is one of the most organic, efficient, low-cost, and energy-saving food preservation methods. In this regard, we undertake in this study an experimental evaluation and analysis of the thermal performance of different natural convection drying systems: a solar greenhouse dryer, an indirect solar dryer with a single compartment, and a solar dryer with two compartments. These systems have been implemented at the Solar Energy and Environment Laboratory of Mohammed V University (Morocco). The objective of this work is to study the feasibility of converting a solar greenhouse into a solar dryer for use during the summer. On the other hand, to study the thermal performances of this greenhouse dryer by comparing it with other solar dryers. The experimental study showed that the drying of verbena leaves took 6 hours in the indirect dryer 1, 3 hours in the indirect dryer, and 2 and 4 hours in the greenhouse dryer, but the amortization period of the solar greenhouse dryer is lower than the other two solar dryers. The results of this study provide key information on the implementation and performance of these systems for drying food of great global interest.

Keywords: indirect solar dryer, solar energy, agricultural greenhouse, green energy

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Authors: Hamidreza Ahmadi, Majid Abbasalizadeh, Ghasem Yazdani, Masoud Ahmadi

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In this paper a special kind of aerodynamic system as a spoiler has been designed and tried to show effects of this devise on braking system of vehicle. Moreover, position of this spoiler has been considered in order to find optimum point from safety and highest rate of braking view for spoiler. Fluent software is our main tool to calculate rate of extra force that is produced by spoiler and this article has been tried to use various figures that are showed effects of spoiler at different speeds, angles and also heights. Other major points in this paper are static pressure of vehicle at different speed and statues. Undoubtedly, shape of spoiler would be very important, so in this investigation spoiler has been designed and proposed after a lot of simulation for different shape of spoiler. In the end, there is very important part as validation since these simulations must be validated by experimental way to prove our claims. In this case, a special kind of BMW has been simulated and results have been compared by experimental results that have been presented by BMW Company. Difference between simulation results and experimental results are very little and it could be a suitable validation for this project.

Keywords: drag force, down force, vehicle, spoiler

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Authors: F. L. Motta, M. H. A. Santana

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Humic Acids (HA) were produced by a Trichoderma viride strain under submerged fermentation in a medium based on the oil palm Empty Fruit Bunch (EFB) and the main variables of the process were optimized by using response surface methodology. A temperature of 40°C and concentrations of 50g/L EFB, 5.7g/L potato peptone and 0.11g/L (NH4)2SO4 were the optimum levels of the variables that maximize the HA production, within the physicochemical and biological limits of the process. The optimized conditions led to an experimental HA concentration of 428.4±17.5 mg/L, which validated the prediction from the statistical model of 412.0mg/L. This optimization increased about 7–fold the HA production previously reported in the literature. Additionally, the time profiles of HA production and fungal growth confirmed our previous findings that HA production preferably occurs during fungal sporulation. The present study demonstrated that T. viride successfully produced HA via the submerged fermentation of EFB and the process parameters were successfully optimized using a statistics-based response surface model. To the best of our knowledge, the present work is the first report on the optimization of HA production from EFB by a biotechnological process, whose feasibility was only pointed out in previous works.

Keywords: empty fruit bunch, humic acids, submerged fermentation, Trichoderma viride

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Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

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The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

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Authors: Birinderjit Singh Kalyan, Inderpreet Kaur, Balwinder Singh Sohi

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In this paper, an equivalent model for floating gate transistor has been proposed. Using the floating gate voltage value, capacitive coupling coefficients has been found at different bias conditions. The amount of charge present on the gate has been then calculated using the transient models of hot electron programming and Fowler-Nordheim Tunnelling. The proposed model can be extended to the transient conditions as well. The SPICE equivalent model is designed and current-voltage characteristics and Transfer characteristics are comparatively analysed. The dc current-voltage characteristics, as well as dc transfer characteristics, have been plotted for an FGMOS with W/L=0.25μm/0.375μm, the inter-poly capacitance of 0.8fF for both programmed and erased states. The Comparative analysis has been made between the present model and capacitive coefficient coupling methods which were already available.

Keywords: FGMOS, floating gate transistor, capacitive coupling coefficient, SPICE model

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Authors: Sajida Rasheed, Imran Hashmi, Luiza Campos, Qizhi Zhou, Kim Keu

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A quadratic model (p ˂ 0.0001) was developed by using central composite design of 50 experimental runs (42 non-center + 8 center points) to assess efficiency of background chlorine residuals in combating accidental microbial episode in a prototype distribution network (DN) (rig). A known amount of background chlorine residuals were maintained in DN and a required number of bacteria, Escherichia coli K-12 strain were introduced by an injection port in the pipe loop system. Samples were taken at various time intervals at different pipe lengths. Spread plate count was performed to count bacterial number. The model developed was significant. With microbial concentration and time (p ˂ 0.0001), pipe length (p ˂ 0.022), background chlorine residuals (p ˂ 0.07) and time^2 (p ˂ 0.09) as significant factors. The ramp function of variables shows that at the microbial count of 10^6, at 0.76 L/min, and pipe length of 133 meters, a background residual chlorine 0.16 mg/L was enough for complete inactivation of microbial episode in approximately 18 minutes.

Keywords: central composite design (CCD), distribution network, Escherichia coli, residual chlorine

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Authors: I. M. Abd Rahim, H. Abdul Rahim, R. Ghazali

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There is numerous non-invasive blood glucose measurement technique developed by researchers, and near infrared (NIR) is the potential technique nowadays. However, there are some disagreements on the optimal wavelength range that is suitable to be used as the reference of the glucose substance in the blood. This paper focuses on the experimental data collection technique and also the analysis method used to analyze the data gained from the experiment. The selection of suitable linear and non-linear model structure is essential in prediction system, as the system developed need to be conceivably accurate.

Keywords: linear, near-infrared (NIR), non-invasive, non-linear, prediction system

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Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

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Authors: Calvin Rong, Regina Agassian, Mindy Engle-Friedman

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Climate changes, including rising sea levels and increases in global temperature, can have major effects on resource availability, leading to increased competition for resources and rising food prices. The abstract nature and often delayed consequences of many ecological problems cause people focus on immediate, specific, and personal events and circumstances that compel immediate and emotional involvement. This finding may be explained by the challenges humans have in imagining themselves in the future, a shortcoming that interferes with decision-making involving far-off rewards, and leads people to indicate a lower concern toward the future than to present circumstances. The present study sought to assess whether priming people to think of themselves in the future might strengthen the connection to their future selves and stimulate environmentally-protective behavior. We hypothesize that priming participants to think about themselves in the future would increase concern for the future environment. 45 control participants were primed to think about themselves in the present, and 42 participants were primed to think about themselves in the futures. After priming, the participants rated their concern over access to clean water, food, and energy on a scale of 1 to 10. They also rated their predicted care levels for the environment at age points 40, 50, 60, 70, 80, and 90 on a scale of 1(not at all) to 10 (very much). Predicted care levels at age 90 for the experimental group was significantly higher than for the control group. Overall the experimental group rated their concern for resources higher than the control. In comparison to the control group (M=7.60, SD=2.104) participants in the experimental group had greater concern for clean water (M=8.56, SD=1.534). In comparison to the control group (M=7.49, SD=2.041) participants in the experimental group were more concerned about food resources (M=8.41, SD=1.830). In comparison to the control group (M=7.22, SD=1.999) participants in the experimental group were more concerned about energy resources (M=8.07, SD=1.967). This study assessed whether a priming strategy could be used to encourage pro-environmental practices that protect limited resources. Future-self priming helped participants see past short term issues and focus on concern for the future environment.

Keywords: climate change, future, priming, global warming

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Authors: Suparman Suparman

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A white noise in autoregressive (AR) model is often assumed to be normally distributed. In application, the white noise usually do not follows a normal distribution. This paper aims to estimate a parameter of AR model that has a exponential white noise. A Bayesian method is adopted. A prior distribution of the parameter of AR model is selected and then this prior distribution is combined with a likelihood function of data to get a posterior distribution. Based on this posterior distribution, a Bayesian estimator for the parameter of AR model is estimated. Because the order of AR model is considered a parameter, this Bayesian estimator cannot be explicitly calculated. To resolve this problem, a method of reversible jump Markov Chain Monte Carlo (MCMC) is adopted. A result is a estimation of the parameter AR model can be simultaneously calculated.

Keywords: autoregressive (AR) model, exponential white Noise, bayesian, reversible jump Markov Chain Monte Carlo (MCMC)

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Authors: Mohammad Saber Rohi, Saghar Heidari

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In this paper, we studied the pricing problem of American options under a regime-switching model with the possibility of a non-optimal exercise policy (early or late exercise time) which is called an irrational strategy. For this, we consider a Markovmodulated model for the dynamic of the underlying asset as an alternative model to the classical Balck-Scholes-Merton model (BSM) and an intensity-based model for the irrational strategy, to provide more realistic results for American option prices under the irrational behavior in real financial markets. Applying a partial differential equation (PDE) approach, the pricing problem of American options under regime-switching models can be formulated as coupled PDEs. To solve the resulting systems of PDEs in this model, we apply a finite element method as the numerical solving procedure to the resulting variational inequality. Under some appropriate assumptions, we establish the stability of the method and compare its accuracy to some recent works to illustrate the suitability of the proposed model and the accuracy of the applied numerical method for the pricing problem of American options under the regime-switching model with irrational behaviors.

Keywords: irrational exercise strategy, rationality parameter, regime-switching model, American option, finite element method, variational inequality

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Authors: Olga Mironiuk, Małgorzata Kossowska

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The aim of the present study was to investigate the influence of Situational Attribution Training on reducing automatic in-group stereotyping in females. The experiment was conducted with the control of age and level of prejudice. 90 female participants were randomly assigned to two conditions: experimental and control group (each group was also divided into younger- and older-aged condition). Participants from the experimental condition were subjected to more extensive training. In the first part of the experiment, the experimental group took part in the first session of Situational Attribution Training while the control group participated in the Grammatical Training Control. In the second part of the research both groups took part in the Situational Attribution Training (which was considered as the second training session for the experimental group and the first one for the control condition). The training procedure was based on the descriptions of ambiguous situations which could be explained using situational or dispositional attributions. The participant’s task was to choose the situational explanation from two alternatives, out of which the second one presented the explanation based on neutral or stereotypically associated with women traits. Moreover, the experimental group took part in the third training session after two- day time delay, in order to check the persistence of the training effect. The main hypothesis stated that among participants taking part in the more extensive training, the automatic in-group stereotyping would be less frequent after having finished training sessions. The effectiveness of the training was tested by measuring the response time and the correctness of answers: the longer response time for the examples where one of two possible answers was based on the stereotype trait and higher correctness of answers was considered to be a proof of the training effectiveness. As the participants’ level of prejudice was controlled (using the Ambivalent Sexism Inventory), it was also assumed that the training effect would be weaker for participants revealing a higher level of prejudice. The obtained results did not confirm the hypothesis based on the response time: participants from the experimental group responded faster in case of situations where one of the possible explanations was based on stereotype trait. However, an interesting observation was made during the analysis of the answers’ correctness: regardless the condition and age group affiliation, participants made more mistakes while choosing the situational explanations when the alternative was based on stereotypical trait associated with the dimension of warmth. What is more, the correctness of answers was higher in the third training session for the experimental group in case when the alternative of situational explanation was based on the stereotype trait associated with the dimension of competence. The obtained results partially confirm the effectiveness of the training.

Keywords: female, in-group stereotyping, prejudice, situational attribution training

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Authors: Hamid Rostami, Ali Fallah Yeznabad, Mohammad H. Baziar

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The energy-based method for evaluating seismic soil liquefaction has two main sections. First is the demand energy, which is dissipated energy of earthquake at a site, and second is the capacity energy as a representation of soil resistance against liquefaction hazard. In this study, using a statistical analysis of recorded data by 14 down-hole array sites in California, an empirical equation was developed to estimate the demand energy at sites. Because determination of capacity energy at a site needs to calculate several site calibration factors, which are obtained by experimental tests, in this study the standard penetration test (SPT) N-value was assumed as an alternative to the capacity energy at a site. Based on this assumption, the empirical equation was employed to calculate the demand energy for 193 liquefied and no-liquefied sites and then these amounts were plotted versus the corresponding SPT numbers for all sites. Subsequently, a discrimination analysis was employed to determine the equations of several boundary curves for various liquefaction likelihoods. Finally, a comparison was made between the probabilistic model and the commonly used stress method. As a conclusion, the results clearly showed that energy-based method can be more reliable than conventional stress-based method in evaluation of liquefaction occurrence.

Keywords: energy demand, liquefaction, probabilistic analysis, SPT number

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Authors: Bekim Berisha, Sebastian Hirsiger, Pavel Hora

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Advanced material models involving several sets of model parameters require a big experimental effort. As models are getting more and more complex like e.g. the so called “Homogeneous Anisotropic Hardening - HAH” model for description of the yielding behavior in the 2D/3D stress space, the number and complexity of the required experiments are also increasing continuously. In the context of sheet metal forming, these requirements are even more pronounced, because of the anisotropic behavior or sheet materials. In addition, some of the experiments are very difficult to perform e.g. the plane stress biaxial compression test. Accordingly, tensile tests in at least three directions, biaxial tests and tension-compression or shear-reverse shear experiments are performed to determine the parameters of the macroscopic models. Therefore, determination of the macroscopic model parameters based on virtual experiments is a very promising strategy to overcome these difficulties. For this purpose, in the framework of multiscale material modeling, a dislocation density based crystal plasticity model in combination with a FFT-based spectral solver is applied to perform virtual experiments. Modeling of the plastic behavior of metals based on crystal plasticity theory is a well-established methodology. However, in general, the computation time is very high and therefore, the computations are restricted to simplified microstructures as well as simple polycrystal models. In this study, a dislocation density based crystal plasticity model – including an implementation of the backstress – is used in a spectral solver framework to generate virtual experiments for three deep drawing materials, DC05-steel, AA6111-T4 and AA4045 aluminum alloys. For this purpose, uniaxial as well as multiaxial loading cases, including various pre-strain histories, has been computed and validated with real experiments. These investigations showed that crystal plasticity modeling in the framework of Representative Volume Elements (RVEs) can be used to replace most of the expensive real experiments. Further, model parameters of advanced macroscopic models like the HAH model can be determined from virtual experiments, even for multiaxial deformation histories. It was also found that crystal plasticity modeling can be used to model anisotropic hardening more accurately by considering the backstress, similar to well-established macroscopic kinematic hardening models. It can be concluded that an efficient coupling of crystal plasticity models and the spectral solver leads to a significant reduction of the amount of real experiments needed to calibrate macroscopic models. This advantage leads also to a significant reduction of computational effort needed for the optimization of metal forming process. Further, due to the time efficient spectral solver used in the computation of the RVE models, detailed modeling of the microstructure are possible.

Keywords: anisotropic hardening, crystal plasticity, micro structure, spectral solver

Procedia PDF Downloads 315

Authors: Shafaq Rubab

Abstract:

The inclusion of special needs students in a classroom is prevailing gradually in developing countries. Digital game-based learning is one the most effective instructional methodology for special needs students. Digital game-based learning facilitates special needs students who actually face challenges and obstacles in their learning processes. This study aimed to evaluate the effectiveness of digital game-based learning on the educational progress of special needs students in developing countries. The quasi-experimental research was conducted by using purposively selected sample size of eight special needs students. Results of both experimental and control group showed that performance of the experimental group students was better than the control group students and there was a significant difference between both groups’ results. This research strongly recommended that digital game-based learning can help special needs students in an inclusive classroom. It also revealed that special needs students can learn efficiently by using pedagogically sound learning games and game-based learning helps a lot for the self-paced fast-track learning system.

Keywords: inclusive education, special needs, digital game-based learning, fast-track learning

Procedia PDF Downloads 294

Authors: Jaypee Limueco

Abstract:

This research focused on the impact of Peer Instruction and PhET Simulations on the level of motivation and Physics anxiety of Grade 9 students. Two groups of students were used in the study. The experimental group involved 65 registered students while the control group has 64 registered students. To determine the level of motivation of students in learning physics, the Physics Motivation Questionnaire was administered. On the other hand, to determine the level of Physics anxiety of the students in each group, Physics Anxiety Rating Scale was used. Peer Instruction supplemented with PhET simulations was implemented in the experimental group while the traditional lecture method was used in the control group. Both instruments were again administered after the implementation of the two different teaching approaches. “Wilcoxon Signed Rank test” was used to test the significant difference between pretest and posttest of each group. “Mann Whitney U” was used to test if significant differences exist between each group before and after instruction. Results showed that there is no significant difference between the level of motivation and anxiety of the experimental and control group before the implementation at p<0.05 significance level. It implies that the students have the same level of motivation and physics anxiety before instruction. However, the results of both tests have significant differences between the groups after instruction. It is also found that there is a significant positive change in the responses of the students in the experimental group while no change was evident on the control. The result of the analysis of the Mann Whitney U shows that the change in the attributes of the students is caused by the treatment. Therefore, it is concluded that Peer Instruction and PhET simulation helped in alleviating motivation of students and minimizing their anxiety towards Physics.

Keywords: anxiety, motivation, peer instruction, PhET simulations

Procedia PDF Downloads 356

Authors: A. Amar

Abstract:

A new model, namely the crystal model, has been modified to calculate the radius and density distribution of light nuclei up to ⁸Be. The crystal model has been modified according to solid-state physics, which uses the analogy between nucleon distribution and atoms distribution in the crystal. The model has analytical analysis to calculate the radius where the density distribution of light nuclei has obtained from analogy of crystal lattice. The distribution of nucleons over crystal has been discussed in a general form. The equation that has been used to calculate binding energy was taken from the solid-state model of repulsive and attractive force. The numbers of the protons were taken to control repulsive force, where the atomic number was responsible for the attractive force. The parameter has been calculated from the crystal model was found to be proportional to the radius of the nucleus. The density distribution of light nuclei was taken as a summation of two clusters distribution as in ⁶Li=alpha+deuteron configuration. A test has been done on the data obtained for radius and density distribution using double folding for d+⁶,⁷Li with M3Y nucleon-nucleon interaction. Good agreement has been obtained for both the radius and density distribution of light nuclei. The model failed to calculate the radius of ⁹Be, so modifications should be done to overcome discrepancy.

Keywords: nuclear physics, nuclear lattice, study nucleus as crystal, light nuclei till to ⁸Be

Procedia PDF Downloads 177

Authors: Jamil Ahmed

Abstract:

Access control models aim to decide whether a user should be denied or granted access to the user‟s requested activity. Various access control models have been established and proposed. The most prominent of these models include role-based, attribute-based, policy based access control models as well as role-centric attribute based access control model. In this paper, a novel access control model is presented called “Role centric Attribute based Policy Driven Access Control (RAPDAC) model”. RAPDAC incorporates the concept of “policy” in the “role centric attribute based access control model”. It leverages the concept of "policy‟ by precisely combining the evaluation of conditions, attributes, permissions and roles in order to allow authorization access. This approach allows capturing the "access control policy‟ of a real time application in a well defined manner. RAPDAC model allows making access decision at much finer granularity as illustrated by the case study of a real time library information system.

Keywords: authorization, access control model, role based access control, attribute based access control

Procedia PDF Downloads 159

Authors: Panagiota Koliousi, Natasha Miaouli

Abstract:

We compare product and labour market liberalization under the two trade union bargaining models: the Right-to-Manage (RTM) model and the Efficient Bargaining (EB) model. The vehicle is a dynamic general equilibrium (DGE) model that incorporates two types of agents (capitalists and workers), imperfectly competitive product and labour markets. The model is solved numerically employing common parameter values and data from the euro area. A key message is that product market deregulation is favourable under any labour market structure while opting for labour market deregulation one should provide special attention to the structure of the labour market such as the bargaining system of unions. If the prevailing way of bargaining is the RTM model then restructuring both markets is beneficial for all agents.

Keywords: market structure, structural reforms, trade unions, unemployment

Procedia PDF Downloads 196