Search results for: flipped classroom model

Authors: Kyoung-Jin Joo, In-Gun Kim, Hyun-Seok Hong, Dong-Woo Kang, Ju Lee

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Recently, the permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) that can be substituted for the induction motor has been studying because of the needs of the development of the premium high efficiency motor for the minimum energy performance standard (MEPS). PMa-SynRM is required to the speed and position information for motor speed and torque controls. However, to apply the sensors has many problems that are sensor mounting space shortage and additional cost, etc. Therefore, in this paper, speed-sensorless control based on model reference adaptive system (MRAS) is introduced to eliminate the sensor. The sensorless method is constructed in a reference model as standard and an adaptive model as the state observer. The proposed algorithm is verified by the simulation.

Keywords: PMa-SynRM, sensorless control, robust estimation, MRAS method

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Authors: Majid Galoie, Khodadad Safavi, Abdolreza Karami Nejad, Reza Roshan

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In this study, a comprehensive scouring model has been developed in order to evaluate the accuracy of various empirical relationships which were suggested for prediction of scour hole depth in plunge pools by Martins, Mason, Chian and Veronese. For this reason, scour hole depths caused by free falling jets from a flip bucket to a plunge pool were investigated. In this study various discharges, angles, scouring times, etc. have been considered. The final results demonstrated that the all mentioned empirical formulas, except Mason formula, were reasonably agreement with the experimental data.

Keywords: scour hole depth, plunge pool, physical model, reliability assessment

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Authors: Olumuyiwa Ojo, Masengo Ilunga

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Artificial neural network (ANN) has broken the bounds of the convention programming, which is actually a function of garbage in garbage out by its ability to mimic the human brain. Its ability to adopt, adapt, adjust, evaluate, learn and recognize the relationship, behavior, and pattern of a series of data set administered to it, is tailored after the human reasoning and learning mechanism. Thus, the study aimed at modeling wastewater treatment process in order to accurately diagnose water control problems for effective treatment. For this study, a stage ANN model development and evaluation methodology were employed. The source data analysis stage involved a statistical analysis of the data used in modeling in the model development stage, candidate ANN architecture development and then evaluated using a historical data set. The model was developed using historical data obtained from Daspoort Wastewater Treatment plant South Africa. The resultant designed dimensions and model for wastewater treatment plant provided good results. Parameters considered were temperature, pH value, colour, turbidity, amount of solids and acidity. Others are total hardness, Ca hardness, Mg hardness, and chloride. This enables the ANN to handle and represent more complex problems that conventional programming is incapable of performing.

Keywords: ANN, artificial neural network, wastewater treatment, model, development

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Authors: Salah Hassab Elnaby, Omnia Hamdy, Aziza Ahmed Hassan, Salwa Abdelkawi, Ibrahim Abdelhalim

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Laser corneal reshaping has been proposed as a successful treatment of many refraction disorders. However, some physical and chemical demonstrations of the laser effect upon interaction with the corneal tissue are still not fully explained. Therefore, different computational and mathematical models have been implemented to predict the depth of the ablated channel and calculate the ablation threshold and the local temperature rise. In the current paper, we present a modified model that aims to answer some of the open questions about the ablation threshold, the ablation rate, and the physical and chemical mechanisms of that action. The proposed model consists of three parts. The first part deals with possible photochemical reactions between the incident photons and various components of the cornea (collagen, water, etc.). Such photochemical reactions may end by photo-ablation or just the electronic excitation of molecules. Then a chemical reaction is responsible for the ablation threshold. Finally, another chemical reaction produces fragments that can be cleared out. The model takes into account all processes at the same time with different probabilities. Moreover, the effect of applying different laser wavelengths that have been studied before, namely the common excimer laser (193-nm) and the solid state lasers (213-nm & 266-nm), has been investigated. Despite the success and ubiquity of the ArF laser, the presented results reveal that a carefully designed 213-nm laser gives the same results with lower operational drawbacks. Moreover, the use of mode locked laser could also decrease the risk of heat generation and diffusion.

Keywords: UV lasers, mathematical model, corneal ablation, photochemical ablation

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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: S. Bennoud, M. Zergoug

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The numerical simulation of electromagnetic interactions is still a challenging problem, especially in problems that result in fully three dimensional mathematical models. The goal of this work is to use mathematical modeling to characterize the reliability and capacity of eddy current technique to detect and characterize defects embedded in aeronautical in-service pieces. The finite element method is used for describing the eddy current technique in a mathematical model by the prediction of the eddy current interaction with defects. However, this model is an approximation of the full Maxwell equations. In this study, the analysis of the problem is based on a three dimensional finite element model that computes directly the electromagnetic field distortions due to defects.

Keywords: eddy current, finite element method, non destructive testing, numerical simulations

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Authors: Maher Agi, Hardik Soni

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This paper presents a deterministic model for optimized control of the inventory of a perishable product subject to both physical deterioration and degradation of its freshness condition. The demand for the product depends on its current inventory level and freshness condition. Our model allows for any positive amount of end of cycle inventory. Some useful conditions that characterize the optimal solution of the model are derived and an algorithm is presented for finding the optimal values of the price, the inventory cycle, the end of cycle inventory level and the order quantity. Numerical examples are then given. Our work shows how the product freshness in conjunction with the inventory deterioration affects the inventory management decisions.

Keywords: inventory management, lot sizing, perishable products, deteriorating inventory, age-dependent demand, stock-dependent demand

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Authors: Laura Bellassen, Idit Shachar

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Multiple sclerosis (MS) is a chronic neurological disorder characterized by demyelination of the central nervous system (CNS), leading to a wide range of physical and cognitive impairments. Myeloid cells in the CNS, such microglia and border associated macrophage cells, participate in the neuroinflammation in MS. Activation of those cells in MS contributes to the inflammatory response in the CNS and recruitment of immune cells in the this compartment. SLAMF5 is a cell surface receptor that functions as a homophilic adhesion molecule, whose signaling can activate or inhibit leukocyte function. In the current study we followed the expression and function of SLAMF5 in myeloid cells in the CNS and in the periphery in the murine model for MS, the experimental autoimmune encephalomyelitis model (EAE). Our results show that SLAMF5 deficiency or blocking decreases the expression of activation molecules and costimulatory molecules such as MHCII and CD80, resulting in delayed onset and reduced progression of the disease. Moreover, blocking SLAMF5 in peripheral monocytes derived from MS patients and iPSC-derived microglia cells, controls the expression of HLA-DR and CD80. Thus, SLAMF5 is a regulator of myeloid cells function and can serve as a therapeutic target in autoimmune disorders as Multiple Sclerosis.

Keywords: multiple sclerosis, EAE model, myeloid cells, new antibody, neuroimmunology

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Authors: Proud Arunrangsiwed, Sarinya Kongtieng

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Teachers and university lecturers face an unsolved problem, which is students’ multitasking behaviors during class time, such as texting or playing a game. It is important to examine the most powerful predictor that can result in students’ educational performances. Meta-analysis was used to analyze the research articles, which were published with the keywords, multitasking, class performance, and texting. We selected 14 research articles published during 2008-2013 from online databases, and four articles met the predetermined inclusion criteria. Effect size of each pair of variables was used as the dependent variable. The findings revealed that the students’ expectancy and value on SNSs usages is the best significant predictor of their educational performances, followed by their motivation and ability in using SNSs, prior educational performances, usage behaviors of SNSs in class, and their personal characteristics, respectively. Future study should conduct a longitudinal design to better understand the effect of multitasking in the classroom.

Keywords: meta-regression analysis, social networking sites, academic Performances, multitasking, motivation

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Authors: J. L. Bhagoria, Ajeet Kumar Giri

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A computational investigation of various flow characteristics with artificial roughness in the form of V-types discrete ribs, heated wall of rectangular duct for turbulent flow with Reynolds number range (3800-15000) and p/e (5 to 12) has been carried out with k-e turbulence model is selected by comparing the predictions of different turbulence models with experimental results available in literature. The current study evaluates thermal performance behavior, heat transfer and fluid flow behavior in a v shaped duct with discrete roughened ribs mounted on one of the principal wall (solar plate) by computational fluid dynamics software (Fluent 6.3.26 Solver). In this study, CFD has been carried out through designing 3-demensional model of experimental solar air heater model analysis has been used to perform a numerical simulation to enhance turbulent heat transfer and Reynolds-Averaged Navier–Stokes analysis is used as a numerical technique and the k-epsilon model with near-wall treatment as a turbulent model. The thermal efficiency enhancement because of selected roughness is found to be 16-24%. The result predicts a significant enhancement of heat transfer as compared to that of for a smooth surface with different P’ and various range of Reynolds number.

Keywords: CFD, solar collector, airheater, thermal efficiency

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Authors: Abdellah Hanafi, G. M. Mostafa, Mohamed Mortada, Ahmed Hamed

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The steam ejectors are the heart of most of the desalination systems that employ vacuum. The systems that employ low grade thermal energy sources like solar energy and geothermal energy use the ejector to drive the system instead of high grade electric energy. The jet-ejector is used to create vacuum employing the flow of steam or air and using the severe pressure drop at the outlet of the main nozzle. The present work involves developing a one dimensional mathematical model for designing jet-ejectors and transform it into computer code using Engineering Equation solver (EES) software. The model receives the required operating conditions at the inlets and outlet of the ejector as inputs and produces the corresponding dimensions required to reach these conditions. The one-dimensional model has been validated using an existed model working on Abu-Qir power station. A prototype has been designed according to the one-dimensional model and attached to a special test bench to be tested before using it in the solar desalination pilot plant. The tested ejector will be responsible for the startup evacuation of the system and adjusting the vacuum of the evaporating effects. The tested prototype has shown a good agreement with the results of the code. In addition a numerical analysis has been applied on one of the designed geometry to give an image of the pressure and velocity distribution inside the ejector from a side, and from other side, to show the difference in results between the two-dimensional ideal gas model and real prototype. The commercial edition of ANSYS Fluent v.14 software is used to solve the two-dimensional axisymmetric case.

Keywords: solar energy, jet ejector, vacuum, evaporating effects

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Authors: Liliana Patricia Olivo Arias

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The present study focused on the hydrodynamic study in a three-phase fluidized bed reactor and the influence of important aspects, such as volume fractions (Hold up), velocity magnitude of gas, liquid and solid phases (hydrogen, gasoil, and gamma alumina), interactions of phases, through of drag models with the k-epsilon turbulence model. For this purpose was employed a Euler-Euler model and also considers the system is constituted of three phases, gaseous, liquid and solid, characterized by its physical and thermal properties, the transport processes that are developed within the transient regime. The proposed model of the three-phase fluidized bed reactor was solved numerically using the ANSYS-Fluent software with different mesh refinements on bed expansion zone in order to observe the influence of the hydrodynamic parameters and convergence criteria. With this model and the numerical simulations obtained for its resolution, it was possible to predict the results of the volume fractions (Hold ups) and the velocity magnitude for an unsteady system from the initial and boundaries conditions were established.

Keywords: three-phase fluidized bed system, CFD simulation, mesh dependency study, hydrodynamic study

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Authors: Song Hyok Choe

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This study presented a method to determine the optimum design parameters based on a mathematical model of the operating process in a manual electromagnetic hammer using solenoid electromagnets. The operating process of the electromagnetic hammer depends on the circuit scheme of the power controller. Mathematical modeling of the operating process was carried out by considering the energy transfer process in the forward and reverse windings and the electromagnetic force acting on the impact and brake pistons. Using the developed mathematical model, the initial design data of a manual electromagnetic hammer proposed in this paper are encoded and analyzed in Matlab. On the other hand, a measuring experiment was carried out by using a measurement device to check the accuracy of the developed mathematical model. The relative errors of the analytical results for measured stroke distance of the impact piston, peak value of forward stroke current and peak value of reverse stroke current were −4.65%, 9.08% and 9.35%, respectively. Finally, it was shown that the mathematical model of the operating process of an electromagnetic hammer is relatively accurate, and it can be used to determine the design parameters of the electromagnetic hammer. Therefore, the design parameters that can provide the required impact energy in the manual electromagnetic hammer were determined using a mathematical model developed. The proposed method will be used for the further design and development of the various types of percussion rock drills.

Keywords: solenoid electromagnet, electromagnetic hammer, stone processing, mathematical modeling

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Authors: Alireza Mirzaee, Soosan Abdollahi, Mohammad Abdollahi

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Unreinforced Masonry (URM) wall is vulnerable in resisting horizontal load such as wind and seismic loading. It is due to the low tensile strength of masonry, the mortar connection between the brick units. URM structures are still widely used in the world as an infill wall and commonly constructed with door and window openings. This research aimed to investigate the behavior of URM wall with openings when horizontal load acting on it and developed load-drift relationship of the wall. The finite element (FE) method was chosen to numerically simulate the behavior of URM with openings. In this research, ABAQUS, commercially available FE software with explicit solver was employed. In order to ensure the numerical model can accurately represent the behavior of an URM wall, the model was validated for URM wall without openings using available experimental results. Load-displacement relationship of numerical model is well agreed with experimental results. Evidence shows the same load displacement curve shape obtained from the FE model. After validating the model, parametric study conducted on URM wall with openings to investigate the influence of area of openings and pre-compressive load on the horizontal load capacity of the wall. The result showed that the increasing of area of openings decreases the capacity of the wall in resisting horizontal loading. It is also well observed from the result that capacity of the wall increased with the increasing of pre-compressive load applied on the top of the walls.

Keywords: masonry constructions, performance at earthquake, MSJC-08 (ASD), bearing wall, tie-column

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Authors: Shah Krupa Rajendra, Amit Kumar

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Increasing use of traditional vehicles driven by internal combustion engine is responsible for the environmental pollution. Further, it leads to depletion of limited energy resources. Therefore, it is required to explore alternative energy sources for the transportation. The promising solution is to use electric vehicle. However, it suffers from limited driving range. Regenerative braking increases the range of the electric vehicle to a certain extent. In this paper, a novel methodology utilizing regenerative braking is described. The model comprising of DC machine, feedback based boost converter and micro-controller is proposed. The suggested method is very simple and reliable. The proposed model successfully shows the energy being saved into during regenerative braking process.

Keywords: boost converter, DC machine, electric vehicle, micro-controller, regenerative braking

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Authors: Ivana Čavlina Tomašević, Višnjica Vučetić, Maja Telišman Prtenjak, Barbara Malečić

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The Split wildfire on the mid-Adriatic Coast in July 2017 is one of the most severe wildfires in Croatian history, given the size and unexpected fire behavior, and it is used in this research as a case study to run the Weather Research and Forecasting Spread Fire (WRF SFIRE) model. This coupled fire-atmosphere model was successfully run for the first time ever for one Croatian wildfire case. Verification of coupled simulations was possible by using the detailed reconstruction of the Split wildfire. Specifically, precise information on ignition time and location, together with mapped fire progressions and spotting within the first 30 hours of the wildfire, was used for both – to initialize simulations and to evaluate the model’s ability to simulate fire’s propagation and final fire scar. The preliminary simulations were obtained using high-resolution vegetation and topography data for the fire area, additionally interpolated to fire grid spacing at 33.3 m. The results demonstrated that the WRF SFIRE model has the ability to work with real data from Croatia and produce adequate results for forecasting fire spread. As the model in its setup has the ability to include and exclude the energy fluxes between the fire and the atmosphere, this was used to investigate possible fire-atmosphere interactions during the Split wildfire. Finally, successfully coupled simulations provided the first numerical evidence that a wildfire from the Adriatic coast region can modify the dynamical structure of the surrounding atmosphere, which agrees with observations from fire grounds. This study has demonstrated that the WRF SFIRE model has the potential for operational application in Croatia with more accurate fire predictions in the future, which could be accomplished by inserting the higher-resolution input data into the model without interpolation. Possible uses for fire management in Croatia include prediction of fire spread and intensity that may vary under changing weather conditions, available fuels and topography, planning effective and safe deployment of ground and aerial firefighting forces, preventing wildland-urban interface fires, effective planning of evacuation routes etc. In addition, the WRF SFIRE model results from this research demonstrated that the model is important for fire weather research and education purposes in order to better understand this hazardous phenomenon that occurs in Croatia.

Keywords: meteorology, agrometeorology, fire weather, wildfires, couple fire-atmosphere model

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Authors: Kadir Özsoy

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Creating a moderately competitive learning environment is believed to have positive effects on student interest and motivation. The best way today to attract young learners to get involved in a fun, competitive learning experience is possible through mobile applications as these learners mostly rely on games and applications on their phones and tablets to have fun, communicate, look for information and study. In this study, a mobile application called ‘QuizUp’ is used to create a specific game topic for elementary level students at Anadolu University Preparatory School. The topic is specially designed with weekly-added questions in accordance with the course syllabus. Students challenge their classmates or randomly chosen opponents to answer questions related to their course subjects. They also chat and post on the topic’s wall in English. The study aims at finding out students’ perceptions towards the use of the application as a classroom and extra-curricular activity through a survey. The study concludes that educational games boost students’ motivation, lead to increased effort, and positively change their studying habits.

Keywords: competitive learning, educational application, effort, motivation 'QuizUp', study habits

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Authors: Arturo J. Anci Alméstar, Jose D. Fernandez Huapaya, David Mauricio

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Companies make erroneous decisions by not evaluating the inherent difficulties of entering electronic commerce without a prior review of current digital and alternate means of payment. For this reason, it is very important for businesses to have reliable, complete and integrated information on the means of current digital and alternate payments that allow decisions to be made about which of these to use. However, there is no such consolidated information or criteria that companies use to make decisions about the means of payment according to their needs. In this paper, we propose a decision tree model based on a taxonomy that presents us with a categorization of digital and alternative means of payment, as well as the visualization of the flow of information at a high level from the company to obtain a recommendation. This will allow the company to make the most appropriate decision about the implementation of the digital means of payment or alternative ideal for their needs, which allows a reduction in costs and complexity of the payment process. Likewise, the efficiency of the proposed model was evaluated through a satisfaction survey presented to company personnel, confirming the satisfactory quality level of the recommendations obtained by the model.

Keywords: digital payment medium, decision tree, decision making, digital payments taxonomy

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Authors: Oluwatofunmi Otobo

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This paper presents a review of the challenges of e-learning and e-learning technologies in tertiary institutions. This review is based on the researchers observations of the challenges of making use of ICT for learning in Nigeria using Adeyemi College of Education as a case study; this is in comparison to tertiary institutions in the UK, US and other more developed countries. In Nigeria and probably Africa as a whole, power is the major challenge. Its inconsistency and fluctuations pose the greatest challenge to making use of online education inside and outside the classroom. Internet and its supporting infrastructures in many places in Nigeria are slow and unreliable. This, in turn, could frustrate any attempt at making use of online education and e-learning technologies. Lack of basic knowledge of computer, its technologies and facilities could also prove to be a challenge as many young people up until now are yet to be computer literate. Personal interest on both the parts of lecturers and students is also a challenge. Many people are not interested in learning how to make use of technologies. This makes them resistant to changing from the ancient methods of doing things. These and others were reviewed by this paper, suggestions, and recommendations were proffered.

Keywords: education, e-learning, Nigeria, tertiary institutions

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Authors: Rusne Kregzdaite, Erika Godlevska, Morta Vidunaite

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The main aim of this research is to explore existing methodologies for artists’ labour force and create artists’ socio-economic and creative conditions in an assessment model. Artists have dual aims in their creative working process: 1) income and 2) artistic self-expression. The valuation of their conditions takes into consideration both sides: the factors related to income and the satisfaction of the creative process and its result. The problem addressed in the study: tangible and intangible artists' criteria used for assessments creativity conditions. The proposed model includes objective factors (working time, income, etc.) and subjective factors (salary covering essential needs, self-satisfaction). Other intangible indicators are taken into account: the impact on the common culture, social values, and the possibility to receive awards, to represent the country in the international market. The empirical model consists of 59 separate indicators, grouped into eight categories. The deviation of each indicator from the general evaluation allows for identifying the strongest and the weakest components of artists’ conditions.

Keywords: artist conditions, artistic labour force, cultural policy, indicator, assessment model

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Authors: Kaisa M. Herne, Hanna E. Björkstedt

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Comparisons of online and laboratory environments are important for assessing whether the environment influences behavioral results. Trust game behavior was examined in three environments: 1) The standard laboratory setting with physically present participants (laboratory), 2) An online environment with an online meeting before playing the trust game (online plus a meeting); and 3) An online environment without a meeting (online without a meeting). In laboratory, participants were present in a classroom and played the trust game anonymously via computers. Online plus a meeting mimicked the laboratory in that participants could see each other in an online meeting before sessions started, whereas online without a meeting was a standard online experiment in which participants did not see each other at any stages of the experiment. Participants were recruited through pools of student subjects at two universities. The trust game was identical in all conditions; it was played with the same software, anonymously, and with stranger matching. There were no statistically significant differences between the treatment conditions regarding trust or trustworthiness. Results suggest that conducting trust game experiments online will yield similar results to experiments implemented in a laboratory.

Keywords: laboratory vs. online experiment, trust behavior, trust game, trustworthiness behavior

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Authors: Man Li, Wanting Zhou, Lei Li

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Communication stability is the primary concern of communication satellites. Communication satellites are easily affected by particle radiation to generate single event effects (SEE), which leads to soft errors (SE) of the combinational logic circuit. The existing research on soft error rates (SER) of the combined logic circuit is mostly based on the assumption that the logic gates being bombarded have the same pulse width. However, in the actual radiation environment, the pulse widths of the logic gates being bombarded are different due to different linear energy transfers (LET). In order to improve the accuracy of SER evaluation model, this paper proposes a soft error rate evaluation method based on LET. In this paper, the authors analyze the influence of LET on the pulse width of combinational logic and establish the pulse width model based on the LET. Based on this model, the error rate of test circuit ISCAS'85 is calculated. The effectiveness of the model is proved by comparing it with previous experiments.

Keywords: communication satellite, pulse width, soft error rates, LET

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Authors: Sonia Achour

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Owing to the outbreak of the Corona pandemic, the shift to online learning took place abruptly. Neither practitioners nor learners were prepared for this sudden move. Higher education providers were compelled to implement online courses on a very short notice. Sultan Qaboos University is one among these. The question of motivation attracted a great number of educators. A case study was carried out so as to shed some lights on students' perceptions towards virtual learning and how it influenced their motivation to learning. The data was collected by means of semi-structured interviews of a focused group of 16 students along with classroom observation over a 12 week period. Both interviews and class observation revealed that there was a general negative feeling about the online teaching platform and its impact on the learners' motivation. Several factors were identified, namely the absence of interaction, social isolation, inconsistency of instructional knowledge, unfamiliarity with the new learning environment, IT illiteracy, and teacher development. The researcher aims at demonstrating the effect of virtual classrooms on students' motivation to acquire L2. The findings may be used to inform future decisions about courses, curriculum design. And teacher development

Keywords: online learning, motivation, EFL context, virtual setting

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Authors: Wesam Hamed

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This paper contributes to the existing literature by investigating the impact of political risks on the capital adequacy ratio in the banking sector of Gulf Cooperation Council (GCC) countries, which is the first attempt for this nexus to the best of our knowledge. The dynamic panel data model (System‐GMM) showed that political risks significantly decrease the capital adequacy ratio in the banking sector. For this purpose, we used political risks, bank-specific, profitability, and macroeconomic variables that are utilized from the data stream database for the period 2005-2017. The results also actively support the “too big to fail” hypothesis. Finally, the robustness results confirm the conclusions derived from the baseline System‐GMM model.

Keywords: capital adequacy ratio, system GMM, GCC, political risks

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Authors: Pranav Ajmera, Amit Kharat, Tanveer Gupte, Richa Pant, Viraj Kulkarni, Vinay Duddalwar, Purnachandra Lamghare

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The cardiothoracic ratio (CTR) is the ratio of the diameter of the heart to the diameter of the thorax. An abnormal CTR, that is, a value greater than 0.55, is often an indicator of an underlying pathological condition. The accurate prediction of an abnormal CTR from chest X-rays (CXRs) aids in the early diagnosis of clinical conditions. We propose a deep learning-based model for automatic CTR calculation that can assist the radiologist with the diagnosis of cardiomegaly and optimize the radiology flow. The study population included 1012 posteroanterior (PA) CXRs from a single institution. The Attention U-Net deep learning (DL) architecture was used for the automatic calculation of CTR. A CTR of 0.55 was used as a cut-off to categorize the condition as cardiomegaly present or absent. An observer performance test was conducted to assess the radiologist's performance in diagnosing cardiomegaly with and without artificial intelligence (AI) assistance. The Attention U-Net model was highly specific in calculating the CTR. The model exhibited a sensitivity of 0.80 [95% CI: 0.75, 0.85], precision of 0.99 [95% CI: 0.98, 1], and a F1 score of 0.88 [95% CI: 0.85, 0.91]. During the analysis, we observed that 51 out of 1012 samples were misclassified by the model when compared to annotations made by the expert radiologist. We further observed that the sensitivity of the reviewing radiologist in identifying cardiomegaly increased from 40.50% to 88.4% when aided by the AI-generated CTR. Our segmentation-based AI model demonstrated high specificity and sensitivity for CTR calculation. The performance of the radiologist on the observer performance test improved significantly with AI assistance. A DL-based segmentation model for rapid quantification of CTR can therefore have significant potential to be used in clinical workflows.

Keywords: cardiomegaly, deep learning, chest radiograph, artificial intelligence, cardiothoracic ratio

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Authors: Akhmad F. K. Khitam, Yi Tai, Hsin-Yun Lee

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In the modern research of construction management, the goals of scheduling are not only to finish the project within the limited duration, but also to improve the impact of people and environment. Especially for the impact to the pedestrian and vehicles, the considerable social cost should be estimated in the total performance of a construction project. However, the site environment has many differences between projects. These interactions affect the requirement and goal of scheduling. It is difficult for schedule planners to quantify these interactions. Therefore, this study use 3D dynamic simulation technology to plan the schedule of the construction engineering projects that affect the current space users (i.e., the pedestrians and vehicles). The proposed model can help the project manager find out the optimal schedule to minimize the inconvenience brought to the space users. Besides, a roadwork project and a building renovation project were analyzed for the practical situation of engineering and operations. Then this study integrates the proper optimization algorithms and computer technology to establish a decision support model. The proposed model can generate a near-optimal schedule solution for project planners.

Keywords: scheduling, simulation, optimization, pedestrian and vehicle behavior

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Authors: Hemad Zareiforoush, Saeed Minaei, Ahmad Banakar, Mohammad Reza Alizadeh

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The quality inspection of rice (Oryza sativa L.) during its various processing stages is very important. In this research, an artificial intelligence-based model coupled with computer vision techniques was developed as a decision support system for qualitative grading of rice grains. For conducting the experiments, first, 25 samples of rice grains with different levels of percentage of broken kernels (PBK) and degree of milling (DOM) were prepared and their qualitative grade was assessed by experienced experts. Then, the quality parameters of the same samples examined by experts were determined using a machine vision system. A grading model was developed based on fuzzy logic theory in MATLAB software for making a relationship between the qualitative characteristics of the product and its quality. Totally, 25 rules were used for qualitative grading based on AND operator and Mamdani inference system. The fuzzy inference system was consisted of two input linguistic variables namely, DOM and PBK, which were obtained by the machine vision system, and one output variable (quality of the product). The model output was finally defuzzified using Center of Maximum (COM) method. In order to evaluate the developed model, the output of the fuzzy system was compared with experts’ assessments. It was revealed that the developed model can estimate the qualitative grade of the product with an accuracy of 95.74%.

Keywords: machine vision, fuzzy logic, rice, quality

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Authors: Wajid Ali Khan

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Extensive experimentation and numerical investigation are performed to predict the machining-induced residual stresses in the end milling of AISI 1045 steel, and an optimization code has been developed using the particle swarm optimization technique. Experiments were conducted using a single factor at a time and design of experiments approach. Regression analysis was done, and a mathematical model of the cutting process was developed, thus predicting the machining-induced residual stress with reasonable accuracy. The mathematical model served as the objective function to be optimized using particle swarm optimization. The relationship between the different cutting parameters and the output variables, force, and residual stresses has been studied. The combined effect of the process parameters, speed, feed, and depth of cut was examined, and it is understood that 85% of the variation of these variables can be attributed to these machining parameters under research. A 3D finite element model is developed to predict the cutting forces and the machining-induced residual stresses in end milling operation. The results were validated experimentally and against the Johnson-cook model available in the literature.

Keywords: residual stresses, end milling, 1045 steel, optimization

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Authors: Roien Qiam, Shoshi Mizokami

Abstract:

Parking demand in the Central Business District (CBD) has enlarged with the increase of the number of private vehicles due to rapid economic growth, lack of an efficient public transport and traffic management system. This has resulted in low mobility, poor accessibility, serious congestion, high rates of traffic accident fatalities and injuries and air pollution, mainly because people have to drive slowly around to find a vacant spot. With parking pricing and enforcement policy, considerable advancement could be found, and on-street parking spaces could be managed efficiently and effectively. To evaluate parking demand and making parking policy, it is required to understand the current parking condition and driver’s behavior, understand how drivers choose their parking type and location as well as their behavior toward finding a vacant parking spot under parking charges and search times. This study illustrates the result from an observational, revealed and stated preference surveys and experiment. Attained data shows that there is a gap between supply and demand in parking and it has maximized. For the modeling of the parking decision, a choice model was constructed based on discrete choice modeling theory and multinomial logit model estimated by using SP survey data; the model represents the choice of an alternative among different alternatives which are priced on-street, off-street, and illegal parking. Individuals choose a parking type based on their preference concerning parking charges, searching times, access times and waiting times. The parking assignment model was obtained directly from behavioral model and is used in parking simulation. The study concludes with an evaluation of parking policy.

Keywords: CBD, parking demand forecast, parking policy, parking choice model

Procedia PDF Downloads 194

Authors: P. Pasomboon, P. Chumnanpuen, T. E-kobon

Abstract:

Hyaluronic acid (HA) consists of linear heteropolysaccharides repeat of D-glucuronic acid and N-acetyl-D-glucosamine. HA has various useful properties to maintain skin elasticity and moisture, reduce inflammation, and lubricate the movement of various body parts without causing immunogenic allergy. HA can be found in several animal tissues as well as in the capsule component of some bacteria including Pasteurella multocida. This study aimed to modify a genome-scale metabolic model of Escherichia coli using computational simulation and flux analysis methods to predict HA productivity under different carbon sources and nitrogen supplement by the addition of two enzymes (GLMU2 and HYAD) from P. multocida to improve the HA production under the specified amount of carbon sources and nitrogen supplements. Result revealed that threonine and aspartate supplement raised the HA production by 12.186%. Our analyses proposed the genome-scale metabolic model is useful for improving the HA production and narrows the number of conditions to be tested further.

Keywords: Pasteurella multocida, Escherichia coli, hyaluronic acid, genome-scale metabolic model, bioinformatics

Procedia PDF Downloads 123