Search results for: shared parameter model

Authors: Melody Yin

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Concussions impact a large amount of adolescents; they make up as much as half of the diagnosed concussions in America. This research proposes a hybrid machine learning model based on the combination of human/knowledge-based domains and computer-generated feature rankings to improve the accuracy of diagnosing sports related concussion (SRC). Using a data set of symptoms collected on the sideline post-SRC events, the symptom selection criteria method has been developed by using Google AutoML's important score function to identify the top 10 symptom features. In addition, symptom domains have been introduced as another parameter, categorizing the symptoms into physical, cognitive, sleep, and emotional domains. The hybrid machine learning model has been trained with a combination of the top 10 symptoms and 4 domains. From the results, the hybrid model was the best performer for symptom resolution time prediction in 2 and 4-week thresholds. This research is a proof of concept study in the use of domains along with machine learning in order to improve concussion prediction accuracy. It is also possible that the use of domains can make the model more efficient due to reduced training time. This research examines the use of a hybrid method in predicting sports-related concussion. This achievement is based on data preprocessing, using a hybrid method to select criteria to achieve high performance.

Keywords: hybrid model, machine learning, sports related concussion, symptom resolution time

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Authors: Siavash Salamatpoor, Hossein Motaghedi, Jr., Mehrdad Nategh

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In this study, undrained triaxial tests under anisotropic consolidation were conducted on the reconstituted samples of Ramsar sand, which underlies a densely populated, seismic region of the southern coast of Caspian Sea in Mazandaran province, Iran. Ramsar costal city is regularly visited by many tourists. Accordingly, many tall building and heavy structures are going to be constructed over this coastal area. This region is overlaid by poorly graded clean sand and because of high water level, is susceptible to liquefaction. The specimens were consolidated anisotropically to simulate initial shear stress which is mobilized due to surface constructions. Different states of soil behavior were obtained by applying different levels of initial relative density, shear stress, and effective stress. It is shown that Ramsar clean sand can experience the whole possible states of liquefiable soils i.e. fully liquefaction, limited liquefaction, and dilation behaviors. It would be shown that by increasing the shear parameter in high confine pressure, the liquefaction susceptibility has increased while for low confine pressure it would be vice versa.

Keywords: anisotropic, triaxial test, shear parameter, static liquefaction

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Authors: Preeyaphorn Kosa, Thanutch Sukwimolseree

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The climate change is a main parameter which affects the element of hydrological cycle especially runoff. Then, the purpose of this study is to determine the impact of the climate change on surface runoff using land use map on 2008 and daily weather data during January 1, 1979 to September 30, 2010 for SWAT model. SWAT continuously simulate time model and operates on a daily time step at basin scale. The results present that the effect of temperature change cannot be clearly presented on the change of runoff while the rainfall, relative humidity and evaporation are the parameters for the considering of runoff change. If there are the increasing of rainfall and relative humidity, there is also the increasing of runoff. On the other hand, if there is the increasing of evaporation, there is the decreasing of runoff.

Keywords: climate, runoff, SWAT, upper Mun River basin

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Authors: Wu Peng, Anders Liljerehn, Martin Magnevall

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In metal cutting, tool wear gradually changes the micro geometry of the cutting edge. Today there is a significant gap in understanding the impact these geometrical changes have on the cutting forces which governs tool deflection and heat generation in the cutting zone. Accurate models and understanding of the interaction between the work piece and cutting tool leads to improved accuracy in simulation of the cutting process. These simulations are useful in several application areas, e.g., optimization of insert geometry and machine tool monitoring. This study aims to develop an extended Kienzle force model to account for the effect of rake angle variations and tool flank wear have on the cutting forces. In this paper, the starting point sets from cutting force measurements using orthogonal turning tests of pre-machined flanches with well-defined width, using triangular coated inserts to assure orthogonal condition. The cutting forces have been measured by dynamometer with a set of three different rake angles, and wear progression have been monitored during machining by an optical measuring collaborative robot. The method utilizes the measured cutting forces with the inserts flank wear progression to extend the mechanistic cutting forces model with flank wear as an input parameter. The adapted cutting forces model is validated in a turning process with commercial cutting tools. This adapted cutting forces model shows the significant capability of prediction of cutting forces accounting for tools flank wear and different-rake-angle cutting tool inserts. The result of this study suggests that the nonlinear effect of tools flank wear and interaction between the work piece and the cutting tool can be considered by the developed cutting forces model.

Keywords: cutting force, kienzle model, predictive model, tool flank wear

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Authors: Muhammad Sohail Khan, Rehan Ali Shah

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The present paper applies the optimal homotopy perturbation method (OHPM) and the optimal homotopy asymptotic method (OHAM) introduced recently to obtain analytic approximations of the non-linear equations modeling the flow of polymer in case of wire coating of a corotational Maxwell fluid. Expression for the velocity field is obtained in non-dimensional form. Comparison of the results obtained by the two methods at different values of non-dimensional parameter l₁₀, reveal that the OHPM is more effective and easy to use. The OHPM solution can be improved even working in the same order of approximation depends on the choices of the auxiliary functions.

Keywords: corotational Maxwell model, optimal homotopy asymptotic method, optimal homotopy perturbation method, wire coating die

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Authors: Samereh Abdoli, Amit Vora, Anusha Vora

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Aim: To qualitatively investigate diabetes burnout in parents of children with Type 1 Diabetes (T1D) who shared their experiences through YouTube videos in order to inform future interventions and improve diabetes practice. Methods: A qualitative descriptive approach was used to explore YouTube videos. Of the 568 videos that were identified, only 9 videos met the inclusion criteria of the study. Results: After the videos were transcribed and analyzed using qualitative content analysis, it was revealed that parents shared common concerns and experiences and they translated into three main themes: I do not ever get a break, I am exhausted, I can’t burn out, and I just need a break Conclusion: All in all, the literature revealed that there are negative psychosocial outcomes associated with caring for a child with T1D, but there is a lack of information on diabetes burnout and how parents’ well-being are affected. Reports of self-neglect and sleep deprivation only confirm the need for intervention for parents of children with T1D. The hope with this study is that burnout can be recognized early on and appropriate interventions put in place to help parents cope with the stressors of caring for a child with a chronic disease.

Keywords: Diabetes burnout, type 1 diabetes, qualitative research, parents

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Authors: Busra Ekinci

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Urban heat island term becomes one of the most important problem in urban areas as a reflection of global warming in local scale last years. Many communities and governments are taking action to reduce heat island effects on urban areas where the half of the world's population live today. At this point, urban design turned out to be an important practice and research area for providing an environmentally sensitive urban development. In this study, mitigating strategies of urban heat island effects by urban design are investigated in Aksaray Square and surroundings in Istanbul. Aksaray is an important historical and commercial center of Istanbul, which has an increasing density due to be the node of urban transportation. Also, Istanbul Metropolitan Municipality prepared an urban design project to respond the needs of growing population in the area for 2018. The purpose of the study is emphasizing the importance of urban design objectives and strategies that are developed to reduce the heat island effects on urban areas. Depending on this, the urban heat island effect of the area was examined based on the albedo (reflectivity) parameter which is the most effective parameter in the formation of the heat island effect in urban areas. Albedo values were calculated by Albedo Viewer web application model that was developed by Energy and Environmental Engineering Department of Kyushu University in Japan. Albedo parameter had examined for the present situation and the planned situation with urban design project. The results show that, the current area has urban heat island potential. With the Aksaray Square Project, the heat island effect on the area can be reduced, but would not be completely prevented. Therefore, urban design strategies had been developed to reduce the island effect in addition to the urban design project of the area. This study proves that urban design objectives and strategies are quite effective to reduce the heat island effects, which negatively affect the social environment and quality of life in urban areas.

Keywords: Albedo, urban design, urban heat island, sustainable design

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Authors: Jatindra Lahkar

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The effect of chemical reaction on laminar mixed convection flow and heat and mass transfer along a vertical unsteady stretching sheet is investigated, in the presence of heat generation/absorption with variable viscosity and viscous dissipation. The governing non-linear partial differential equations are reduced to ordinary differential equations using similarity transformation and solved numerically using the fourth order Runge-Kutta method along with shooting technique. The effects of various flow parameters on the velocity, temperature and concentration distributions are analyzed and presented graphically. Skin-friction coefficient, Nusselt number and Sherwood number are derived at the sheet. It is observed that the influence of chemical reaction, the fluid flow along the sheet accelerate with the increase of chemical reaction parameter, on the other hand, temperature of the fluid increases with increase of chemical reaction parameter but concentration of the fluid reduces with it. The boundary layer decreases on the surface of the sheet for all values of unsteadiness parameter, increasing values of the chemical reaction parameter. The increases in the values of Sc cause the species concentration and its boundary layer thickness to decrease resulting in less induced flow and higher fluid temperatures. This is depicted in the decreases in the velocity and species concentration and increases in the fluid temperature as Sc increases.

Keywords: chemical reaction, heat generation/absorption, magnetic number, unsteadiness, variable viscosity

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Authors: Abdulmohsen Alruwaili

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A partial differential system featuring momentum and energy balance is often used to describe simulations of flow initiation and thermal shifting in boundary layers. The buoyancy force in terms of temperature is factored in the momentum balance equation. Buoyancy force causes the flow quantity to fluctuate along the streamwise direction 𝑋; therefore, the problem can be, to our best knowledge, analyzed through nonsimilar modeling. In this analysis, a nonsimilar model is evolved for radiative mixed convection of a magnetized power-law nanoliquid flow on top of a vertical plate installed in a stationary fluid. The upward linear stretching initiated the flow in the vertical direction. Assuming nanofluids are composite of copper (Cu) and alumina (Al₂O₃) nanoparticles, the viscous dissipation in this case is negligible. The nonsimilar system is dealt with analytically by local nonsimilarity (LNS) via numerical algorithm bvp4c. Surface temperature and flow field are shown visually in relation to factors like mixed convection, magnetic field strength, nanoparticle volume fraction, radiation parameters, and Prandtl number. The repercussions of magnetic and mixed convection parameters on the rate of energy transfer and friction coefficient are represented in tabular forms. The results obtained are compared to the published literature. It is found that the existence of nanoparticles significantly improves the temperature profile of considered nanoliquid. It is also observed that when the estimates of the magnetic parameter increase, the velocity profile decreases. Enhancement in nanoparticle concentration and mixed convection parameter improves the velocity profile.

Keywords: nanofluid, power law model, mixed convection, thermal radiation

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

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Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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Authors: C. C. Lv, Y. L. Sun, D. W. Zuo

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Cemented carbide balls are usually implemented in industry under the environment of high speed, high temperature, corrosiveness and strong collisions. However, its application is limited due to high fabrication cost, processing efficiency and quality. A novel eccentric lapping method with two rotatable lapping plates was proposed in this paper. A mathematical model was constructed to analyze the influence of each design parameter on this lapping method. To validate this new lapping method, an orthogonal experiment was conducted with cemented carbide balls (YG6). The simulation model was verified and the optimal lapping parameters were derived. The results show that the surface roundness of the balls reaches to 0.65um from 2um in 1 hour using this lapping method. So, using this novel lapping method, it can effectively improve the machining precision and efficiency of cemented carbide balls.

Keywords: cemented carbide balls, eccentric lapping, high precision, lapping tracks, V-groove

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Authors: Hamed Hedayatnia, Nathan Van Den Bossche

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Understanding the ways in which climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the conservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like freeze-thaw cycles and wind erosion is also a key parameter when considering mitigating actions. Due to the vulnerability of cultural heritage to climate change, the impact of this phenomenon on material degradation criteria with the focus on brick masonry walls in Timurid heritage, located in Iran, was studied. The Timurids were the final great dynasty to emerge from the Central Asian steppe. Through their patronage, the eastern Islamic world in northwestern of Iran, especially in Mashhad and Herat, became a prominent cultural center. Goharshad Mosque is a mosque in Mashhad of the Razavi Khorasan Province, Iran. It was built by order of Empress Goharshad, the wife of Shah Rukh of the Timurid dynasty in 1418 CE. Choosing an appropriate regional climate model was the first step. The outputs of two different climate model: the 'ALARO-0' and 'REMO,' were analyzed to find out which model is more adopted to the area. For validating the quality of the models, a comparison between model data and observations was done in 4 different climate zones in Iran for a period of 30 years. The impacts of the projected climate change were evaluated until 2100. To determine the material specification of Timurid bricks, standard brick samples from a Timurid mosque were studied. Determination of water absorption coefficient, defining the diffusion properties and determination of real density, and total porosity tests were performed to characterize the specifications of brick masonry walls, which is needed for running HAM-simulations. Results from the analysis showed that the threatening factors in each climate zone are almost different, but the most effective factor around Iran is the extreme temperature increase and erosion. In the north-western region of Iran, one of the key factors is wind erosion. In the north, rainfall erosion and mold growth risk are the key factors. In the north-eastern part, in which our case study is located, the important parameter is wind erosion.

Keywords: brick, climate change, degradation criteria, heritage, Timurid period

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Authors: A. Naamane, M. Hasnaoui

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Numerical modeling of fluid flows, whether compressible or incompressible, laminar or turbulent presents a considerable contribution in the scientific and industrial fields. However, the development of an approximate model of a supersonic flow requires the introduction of specific and more precise techniques and methods. For this purpose, the object of this paper is modeling a supersonic flow of inviscid fluid around a dihedral airfoil. Based on the thin airfoils theory and the non-dimensional stationary Steichen equation of a two-dimensional supersonic flow in isentropic evolution, we obtained a solution for the downstream velocity potential of the oblique shock at the second order of relative thickness that characterizes a perturbation parameter. This result has been dealt with by the asymptotic analysis and characteristics method. In order to validate our model, the results are discussed in comparison with theoretical and experimental results. Indeed, firstly, the comparison of the results of our model has shown that they are quantitatively acceptable compared to the existing theoretical results. Finally, an experimental study was conducted using the AF300 supersonic wind tunnel. In this experiment, we have considered the incident upstream Mach number over a symmetrical dihedral airfoil wing. The comparison of the different Mach number downstream results of our model with those of the existing theoretical data (relative margin between 0.07% and 4%) and with experimental results (concordance for a deflection angle between 1° and 11°) support the validation of our model with accuracy.

Keywords: asymptotic modelling, dihedral airfoil, supersonic flow, supersonic wind tunnel

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Authors: Arun Prasath Subramanian

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The turbine Inlet Temperature is an important parameter which determines the efficiency of a gas turbine engine. The increase in this parameter is limited by material constraints of the turbine blade.The modern Gas turbine blade has undergone a drastic change from a simple solid blade to a modern multi-pass blade with internal and external cooling techniques. This paper aims to introduce the reader the concept of turbine blade cooling, the classification of techniques and further explain some of the important internal cooling technologies used in a modern gas turbine blade along with the various factors that affect the cooling effectiveness.

Keywords: gas turbine blade, cooling technologies, internal cooling, pin-fin cooling, jet impingement cooling, rib turbulated cooling, metallic foam cooling

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Authors: Muluken Z. Getie, Francois Lanzetta, Sylvie Begot, Bimrew T. Admassu

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This study is aimed at the numerical analysis of the effects of phase angle and losses (shuttle heat loss and gas leakage to the crankcase) that could have an impact on the pressure and temperature of working fluid for a β-type Stirling cycle refrigerating machine. First, the developed numerical model incorporates into the ideal adiabatic analysis, the shuttle heat transfer (heat loss from compression space to expansion space), and gas leakage from the working space to the buffer space into the crankcase. The other losses that may not have a direct effect on the temperature and pressure of working fluid are simply incorporated in a simple analysis. The model is then validated by reversing the model to the engine model and compared with other literature results using (GPU-3) engine. After validating the model with other engine model and experiment results, analysis of the effect of phase angle, shuttle heat lose and gas leakage on temperature, pressure, and performance (power requirement, cooling capacity and coefficient of performance) of refrigerating machine considering the FEMTO 60 Stirling engine as a case study have been conducted. Shuttle heat loss has a greater effect on the temperature of working gas; gas leakage to the crankcase has more effect on the pressure of working spaces and hence both have a considerable impact on the performance of the Stirling cycle refrigerating machine. The optimum coefficient of performance exists between phase angles of 900-950, and optimum cooling capacity could be found between phase angles of 950-980.

Keywords: beta configuration, engine model, moderate cooling, stirling refrigerator, and validation

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Authors: Enayatollah Yazdani

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Globalization is the most significant change in today’s world. It has caused remarkable growth in different aspects of human life. Such a strong contribution to the development would not have occurred without the role that each country and particularly great powers play in the globalization process. Among those powers is China, whose role in the globalization trend is growing fast. With its rapid economic and technological development, China has moved from a regional economic power to a global powerhouse. Accordingly, China has been supporting the development of global infrastructure through new initiatives and institutions such as the Asia Infrastructure Investment Bank and the New Development Bank, among them, the most ambitious manifestation of these efforts is China Belt and Road Initiative (BRI). BRI is seen as an important vehicle that helps China to play a more proactive role in the globalization process. China started Belt and Road initiative as a global drive in more than 65 (now more than 140) countries in Asia, the Middle East, Central Asia, Latin America, Africa, and Europe, offering the world a unique state of bigger openness, integration, and interdependence with a comprehensive approach to shared development, shared future, and shared opportunities. As a result, one can say that BRI is an attempt by China to promote international cooperation and enhance globalization. However, in this regard, China may face some challenges as well. This paper aims to address: how China is playing a role in globalization through BRI and how BRI will support the Chinese role in the globalization process. And what are the major challenges that China might be faced? Based on the analytical methodology, the paper argues that BRI is a cornucopia of international projects that offer mammoth opportunities for more economic cooperation and deeper regional and global integration, primarily among emerging economies. The paper discusses that at a time when globalization from the West appears to be in retreat, the BRI is a potent symbol of the rise of China-based globalization.

Keywords: globalization, China, belt, and road initiative

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Authors: Peng Wang, Tigang Jiang

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The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

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Authors: Aida Raissi, Holly Wong, Elma Raissi

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Background: Connection is a primal need established during infancy and reiterated in many forms of social interaction. When we make connections with others we experience growth, continuity, and gain an understanding of the other’s sense of the world. Feeling socially connected to another individual or community has been shown to increase self-esteem, happiness, and meaning. However, feeling connected to another individual or a specific community may also decrease the motivation to seek connection with more distant individuals or communities. Furthermore, we allow ourselves to interact with those in other communities as apart from us, and in some cases, to dehumanize their existence. Objective: The aim of this project is to bridge the gap between different communities, specifically religious communities and foster feelings of connection as one with all members through the medium of art, specifically photography. Method: Members of all major faiths including Agnosticism, Atheism, Buddhism, Catholicism, Christianity, Ismaili, Jewish, Ja’far Shia, Sunni will be interviewed. Participants will be asked to partake in a brief interview of two parts: A. Answering two questions: 1. What are you most looking forward to in the future, and why? 2. What does religion mean to you? B. Having their picture taken. Our questions aim to elicit individual stories that together, show that we have more in common, than differences, despite our faiths. With the completion of the interviews, the responses will be compiled together and major themes will be identified. Impact: The resulting stories and corresponding individual pictures provide an excellent opportunity to encourage and inspire people to get to know those of other beliefs and values, participate in each other’s communities and develop a sense of oneness within our shared humanity. Knowledge translation: The personal stories, and the common themes they illustrate, will be shared with various audiences, including the general public, academia and targeted groups such as students. This will be done through displaying the photographs and responses at art galleries, conferences, in print and online.

Keywords: social justice, religion, connection, understanding, community

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Authors: Imran Badshah

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Pedestrian service time reflects the performance of the facility, and it’s a key parameter to analyze the capability of facilities provided to serve pedestrians. The level of service of pedestrians (LOS) mainly depends on pedestrian time and safety. The pedestrian time utilized by taking a service is mainly influenced by the number of available services and the time utilized by each pedestrian in receiving a service; that is called a delay time. In this paper, we analyzed the simulated pedestrian service time with different delay times. A simulation is performed in AnyLogic by developing a model that reflects the real scenario of pedestrian services such as ticket machine gates at rail stations, airports, shopping malls, and cinema halls. The simulated pedestrian time is determined for various delay values. The simulated result shows how pedestrian time changes with the delay pattern. The histogram and time plot graph of a model gives the mean, maximum and minimum values of the pedestrian time. This study helps us to check the behavior of pedestrian time at various services such as subway stations, airports, shopping malls, and cinema halls.

Keywords: agent-based simulation, anylogic model, pedestrian behavior, time delay

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Authors: Rizki Nor Amelia, Farida A. Setiawati

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This study aimed to: (1) describe the characteristics of teacher-made test instrument used to measure the ability of students’chemistry, and (2) identify the presence of the compability difficulty level set by teachers to difficulty level by empirical results. Based on these objectives, this study was a descriptive research. The analysis in this study used the Rasch model and Chi-square statistics. Analysis using Rasch Model was based on the response patterns of high school students to the teacher-made test instrument on chemistry subject Academic Year 2015/2016 in the Yogyakarta. The sample of this research were 358 students taken by cluster random sampling technique. The analysis showed that: (1) a teacher-made tests instrument has a medium on the mean difficulty level. This instrument is capable to measure the ability on the interval of -0,259 ≤ θ ≤ 0,659 logit. Maximum Test Information Function obtained at 18.187 on the ability +0,2 logit; (2) 100% items categorized either as easy or difficult by rasch model is match with the teachers’ judgment; while 37 items are categorized according to rasch model which 8.10% and 10.81% categorized as easy and difficult items respectively according to the teachers, the others are medium categorized. Overall, the distribution of the level of difficulty formulated by the teachers has the distinction (not match) to the level of difficulty based on the empirical results.

Keywords: chemistry, items parameter fitness, Rasch model, teacher-made test

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Authors: Jihoon Lim, Patrick Kirchen, Ryozo Nagamune

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This paper proposes a linear parameter-varying (LPV) controller capable of reducing nitrogen oxide (NOx) emissions with low ammonia (NH3) slip downstream of selective catalytic reduction (SCR) systems. SCR systems are widely adopted in diesel engines due to high NOx conversion efficiency. However, the nonlinearity of the SCR system and sensor uncertainty result in a challenging control problem. In order to overcome the control challenges, an LPV controller is proposed based on gain-scheduling parameters, that is, exhaust gas temperature and exhaust gas flow rate. Based on experimentally obtained data under the non-road transient driving cycle (NRTC), the simulations firstly show that the proposed controller yields high NOx conversion efficiency with a desired low NH3 slip. The performance of the proposed LPV controller is then compared with other controllers, including a gain-scheduling PID controller and a sliding mode controller. Additionally, the robustness is also demonstrated using the uncertainties ranging from 10 to 30%. The results show that the proposed controller is robustly stable under uncertainties.

Keywords: diesel engine, gain-scheduling control, linear parameter-varying, selective catalytic reduction

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Authors: Jorge Sandoval Lezama, Arturo Ivan Sandoval Rodriguez, Jose Arturo Correa Arredondo

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This work aims to share innovative educational experiences at IPN Mexico, that involve collaborative learning at institutional and global level through course competition and global collaboration projects. Students from universities in China, USA, South Korea, Canada and Mexico collaborate to design electric vehicles to solve global urban mobility problems. The participation of IPN students in the 2015-2016 global competition (São Paolo, Brazil and Cincinnati, USA) Reconfigurable Shared-Use Mobility Systems allowed to apply pedagogical strategies of groups of collaboration and of learning based on projects where they shared activities, commitments and goals, demonstrating that students were motivated to develop / self-generate their knowledge with greater meaning and understanding. One of the most evident achievements is that the students are self-managed, so the most advanced students train the students who join the project with CAD, CAE, CAM tools. Likewise, the motivation achieved is evident since in 2014 there were 12 students involved in the project, and there are currently more than 70 students.

Keywords: collaboration projects, global competency, course competition, active learning

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Authors: A. Elragig, S. Townley, H. Dreiwi

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In this paper we introduce a bacteria-leukocyte model with bacteria chemotaxsis. We assume that bacteria develop a tactic defense mechanism as a response to Leukocyte phagocytosis. We explore the effect of this tactic motion on Turing space in two parameter spaces. A fine tuning of bacterial chemotaxis shows a significant effect on developing a non-uniform steady state.

Keywords: chemotaxis-diffusion driven instability, bacterial chemotaxis, mathematical biology, ecology

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Authors: Amares Chattopadhyay, Akanksha Srivastava

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A unified approach to study the reflection of a plane wave in three-dimensional model comprised of the triclinic viscoelastic medium. The phase velocities of reflected qP, qSV and qSH wave have been calculated for the concerned medium by using the eigenvalue approach. The generalized method has been implemented to compute the complex form of amplitude ratios. Further, we discussed the nature of reflection coefficients of qP, qSV and qSH wave. The viscoelastic parameter, polar angle and azimuthal angle are found to be strongly influenced by amplitude ratios. The research article is particularly focused to study the effect of viscoelasticity associated with highly anisotropic media which exhibits the notable information about the reflection coefficients of qP, qSV, and qSH wave. The outcomes may further useful to the better exploration of all types of hydrocarbon reservoir and advancement in the field of reflection seismology.

Keywords: amplitude ratios, three dimensional, triclinic, viscoelastic

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Authors: Farnoosh Alami, Nazgol Azimi

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Universities have recently paid much attention to the subject of social entrepreneurship. As a result, many of the highly ranked universities have established centers in this regard. The present research aims to investigate vision and mission of social entrepreneurship centers of the best universities ranked under 50 by Shanghai List 2013. It tries to find the common goals and features of their mission, vision, and activities which lead to their present success. This investigation is based on the web content of the first top 10 universities; among which six had social entrepreneurship centers. This is a qualitative research, and the findings are based on content analysis of documents. The findings confirm that education, research, talent development, innovative solutions, and supporting social innovation, are shared in the vision of these centers. In regard to their missions, social participation, networking, and leader education are the most shared features. Their common activities are focused on five categories of education, research, support, promotion, and networking.

Keywords: comparative study, qualitative research, social entrepreneurship centers, universities in the world

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Authors: Jawaher A. Alsultan, Allen Feldman

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With the rapid switch to remote learning due to the COVID-19 pandemic, science teachers were suddenly required to teach their classes online. This breakneck shift to eLearning raised the question of how teacher educators could support science teachers who wanted to use reform-based methods of instruction while using virtual technologies. In this retrospective self-study, we, two science teacher educators, examined our practice as we worked with science teachers to implement inquiry, discussion, and argumentation [IDA] through eLearning. Ten high school science teachers from a large school district in the southeastern US participated virtually in the COVID-19 Community of Practice [COVID-19 CoP]. The CoP met six times from the end of April through May 2020 via Zoom. Its structure was based on a model of action research called enhanced normal practice [ENP], which includes exchanging stories, trying out ideas, and systematic inquiry. Data sources included teacher educators' meeting notes and reflective conversations, audio recordings of the CoP meetings, teachers' products, and post-interviews of the teachers. Findings included a new understanding of the role of existing relationships, shared goals, and similarities in the participants' situations, which helped build trust in the CoP, and the effects of our paying attention to the science teachers’ needs led to a well-functioning CoP. In addition, we became aware of the gaps in our knowledge of how the teachers already used apps in their practice, which they then shared with all of us about how they could be used for online teaching using IDA. We also identified the need to pay attention to feelings about tensions between the teachers and us around the expectations for final products and the project's primary goals. We found that if we are to establish relationships between us as facilitators and teachers that are honest, fair, and kind, we must express those feelings within the collective, dialogical processes that can lead to learning by all members of the CoP, whether virtual or face-to-face.

Keywords: community of practice, facilitators, self-study, action research

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Authors: Guanhua Zhou, Zhongqi Ma

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Submerged aquatic vegetation (SAV) in wetlands can absorb nitrogen and phosphorus effectively to prevent the eutrophication of water. It is feasible to monitor the distribution of SAV through remote sensing, but for the reason of weak vegetation signals affected by water body, traditional terrestrial vegetation indices are not applicable. This paper aims at constructing SAV index to enhance the vegetation signals and distinguish SAV from water body. The methodology is as follows: (1) select the bands sensitive to the vegetation parameters based on global sensitivity analysis of SAV canopy radiative transfer model; (2) take the soil line concept as reference, analyze the distribution of SAV and water reflectance simulated by SAV canopy model and semi-analytical water model in the two-dimensional space built by different sensitive bands; (3)select the band combinations which have better separation performance between SAV and water, and use them to build the SAVI indices in the form of normalized difference vegetation index(NDVI); (4)analyze the sensitivity of indices to the water and vegetation parameters, choose the one more sensitive to vegetation parameters. It is proved that index formed of the bands with central wavelengths in 705nm and 842nm has high sensitivity to chlorophyll content in leaves while it is less affected by water constituents. The model simulation shows a general negative, little correlation of SAV index with increasing water depth. Moreover, the index enhances capabilities in separating SAV from water compared to NDVI. The SAV index is expected to have potential in parameter inversion of wetland remote sensing.

Keywords: global sensitivity analysis, radiative transfer model, submerged aquatic vegetation, vegetation indices

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Authors: Davide Gotti, Milan Prodanovic, Sergio Pinilla, David Muñoz-Torrero

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Since its proposal, the Doyle-Fuller-Newman (DFN) lithium-ion battery model has gained popularity in the electrochemical field. In fact, this model provides the user with theoretical support for designing the lithium-ion battery parameters, such as the material particle or the diffusion coefficient adjustment direction. However, the model is mathematically complex as it is composed of several partial differential equations (PDEs) such as Fick’s law of diffusion, the MacInnes and Ohm’s equations, among other phenomena. Thus, to efficiently use the model in a time-domain simulation environment, the selection of the discretization technique is of a pivotal importance. There are several numerical methods available in the literature that can be used to carry out this task. In this study, a comparison between the explicit Euler, Crank-Nicolson, and Chebyshev discretization methods is proposed. These three methods are compared in terms of accuracy, stability, and computational times. Firstly, the explicit Euler discretization technique is analyzed. This method is straightforward to implement and is computationally fast. In this work, the accuracy of the method and its stability properties are shown for the electrolyte diffusion partial differential equation. Subsequently, the Crank-Nicolson method is considered. It represents a combination of the implicit and explicit Euler methods that has the advantage of being of the second order in time and is intrinsically stable, thus overcoming the disadvantages of the simpler Euler explicit method. As shown in the full paper, the Crank-Nicolson method provides accurate results when applied to the DFN model. Its stability does not depend on the integration time step, thus it is feasible for both short- and long-term tests. This last remark is particularly important as this discretization technique would allow the user to implement parameter estimation and optimization techniques such as system or genetic parameter identification methods using this model. Finally, the Chebyshev discretization technique is implemented in the DFN model. This discretization method features swift convergence properties and, as other spectral methods used to solve differential equations, achieves the same accuracy with a smaller number of discretization nodes. However, as shown in the literature, these methods are not suitable for handling sharp gradients, which are common during the first instants of the charge and discharge phases of the battery. The numerical results obtained and presented in this study aim to provide the guidelines on how to select the adequate discretization technique for the DFN model according to the type of application to be performed, highlighting the pros and cons of the three methods. Specifically, the non-eligibility of the simple Euler method for longterm tests will be presented. Afterwards, the Crank-Nicolson and the Chebyshev discretization methods will be compared in terms of accuracy and computational times under a wide range of battery operating scenarios. These include both long-term simulations for aging tests, and short- and mid-term battery charge/discharge cycles, typically relevant in battery applications like grid primary frequency and inertia control and electrical vehicle breaking and acceleration.

Keywords: Doyle-Fuller-Newman battery model, partial differential equations, discretization, numerical methods

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Authors: Pau Rodriguez, Jordi Gonzalez, Josep M. Gonfaus, Xavier Roca

Abstract:

Image sharing in social networks has increased exponentially in the past years. Officially, there are 600 million Instagrammers uploading around 100 million photos and videos per day. Consequently, there is a need for developing new tools to understand the content expressed in shared images, which will greatly benefit social media communication and will enable broad and promising applications in education, advertisement, entertainment, and also psychology. Following these trends, our work aims to take advantage of the existing relationship between text and personality, already demonstrated by multiple researchers, so that we can prove that there exists a relationship between images and personality as well. To achieve this goal, we consider that images posted on social networks are typically conditioned on specific words, or hashtags, therefore any relationship between text and personality can also be observed with those posted images. Our proposal makes use of the most recent image understanding models based on neural networks to process the vast amount of data generated by social users to determine those images most correlated with personality traits. The final aim is to train a weakly-supervised image-based model for personality assessment that can be used even when textual data is not available, which is an increasing trend. The procedure is described next: we explore the images directly publicly shared by users based on those accompanying texts or hashtags most strongly related to personality traits as described by the OCEAN model. These images will be used for personality prediction since they have the potential to convey more complex ideas, concepts, and emotions. As a result, the use of images in personality questionnaires will provide a deeper understanding of respondents than through words alone. In other words, from the images posted with specific tags, we train a deep learning model based on neural networks, that learns to extract a personality representation from a picture and use it to automatically find the personality that best explains such a picture. Subsequently, a deep neural network model is learned from thousands of images associated with hashtags correlated to OCEAN traits. We then analyze the network activations to identify those pictures that maximally activate the neurons: the most characteristic visual features per personality trait will thus emerge since the filters of the convolutional layers of the neural model are learned to be optimally activated depending on each personality trait. For example, among the pictures that maximally activate the high Openness trait, we can see pictures of books, the moon, and the sky. For high Conscientiousness, most of the images are photographs of food, especially healthy food. The high Extraversion output is mostly activated by pictures of a lot of people. In high Agreeableness images, we mostly see flower pictures. Lastly, in the Neuroticism trait, we observe that the high score is maximally activated by animal pets like cats or dogs. In summary, despite the huge intra-class and inter-class variabilities of the images associated to each OCEAN traits, we found that there are consistencies between visual patterns of those images whose hashtags are most correlated to each trait.

Keywords: emotions and effects of mood, social impact theory in social psychology, social influence, social structure and social networks

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Authors: Jaime E. Fernandez, Pablo J. Valverde

Abstract:

This paper presents a methodological approach that aims to contrast/validate theoretical results from a corruption network game through probabilistic analysis of simulated microdata using Bayesian Networks (BNs). The research develops a public corruption model in a game theory framework. Theoretical results suggest a series of 'optimal settings' of model's exogenous parameters that boost the emergence of corruption. The paper contrasts these outcomes with probabilistic inference results based on BNs adjusted over simulated microdata. Principal findings indicate that probabilistic reasoning based on BNs significantly improves parameter specification and causal analysis in a public corruption game.

Keywords: Bayesian networks, probabilistic reasoning, public corruption, theoretical games

Procedia PDF Downloads 210