Search results for: computational cognitive model

Authors: H. Aminfar, M. Mohammadpourfard, K. Khajeh

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This paper has focused on the most important parameters in the LSC uptake; inlet Re number and Sc number in the presence of non-uniform magnetic field. The magnetic field is arising from the thin wire with electric current placed vertically to the arterial blood vessel. According to the results of this study, applying magnetic field can be a treatment for atherosclerosis by reducing LSC along the vessel wall. Homogeneous porous layer as a arterial wall has been regarded. Blood flow has been considered laminar and incompressible containing Ferro fluid (blood and 4 % vol. Fe₃O₄) under steady state conditions. Numerical solution of governing equations was obtained by using the single-phase model and control volume technique for flow field.

Keywords: LDL surface concentration (LSC), magnetic field, computational fluid dynamics, porous wall

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Authors: Yenie Norambuena

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Analogical reasoning is a cognitive process that consists of structured comparisons of mental representations and scheme construction. Because of its heuristic function, it is ubiquitous in cognition and could play an important role in language development. The use of analogies is expressed early in children and this behavior is also reflected in language, suggesting a possible way to understand the complex links between thought and language. The current research examines factors of verbal and non-verbal reasoning that should be taken into consideration in the study of language development for their relations and predictive value. The study was conducted with 48 Chilean preschoolers (Spanish speakers) from 4 to 6-year-old. We assessed children’s verbal analogical reasoning, non-verbal analogical reasoning and linguistics skills (Listening Comprehension, Phonemic awareness, Alphabetic principle, Syllabification, Lexical repetition and Lexical decision). The results evidenced significant correlations between analogical reasoning factors and linguistic skills and they can predict linguistic performance mainly on oral comprehension, lexical decision and phonological skills. These findings suggest a fundamental interrelationship between analogical reasoning and linguistic performance on children’s and points to the need to consider this cognitive process in comprehensive theories of children's language development.

Keywords: verbal analogical reasoning, non-verbal analogical reasoning, linguistic skills, language development

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Authors: R. Shamsi, F. Sharifi

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In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose a multi-objective DEA-R model because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduce the efficiency score), an efficient decision-making unit (DMU) is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other cases, only the ratio of stochastic data may be available (e.g., the ratio of stochastic inputs to stochastic outputs). Thus, we provide a multi-objective DEA model without explicit outputs and prove that the input-oriented MOP DEA-R model in the invariable return to scale case can be replaced by the MOP-DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA-R, multi-objective programming, stochastic data, data envelopment analysis

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Authors: R. Herscu-Kluska

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The rise of the flipped or inverted classroom meet the conceptual needs of our time. The evidence of increased student satisfaction and course grades improvement promoted the flipped learning approach. Due to the successful outcomes of the inverted classroom, the flipped learning became a pedagogy and educational rising strategy among all education sciences. The aim of this study is to analyze the effect of flipped classroom on higher order learning in chemistry courses since it has been suggested that in higher education courses, class time should focus on knowledge application. The results of this study indicate improving meta-cognitive thinking and learning skills. The students showed better ability to cope with higher order learning assignments during the actual class time, using inverted classroom strategy. These results suggest that flipped learning can be used as an effective pedagogy and educational strategy for developing higher order thinking skills, proved to contribute to building lifelong learning.

Keywords: chemistry education, flipped classroom, flipped learning, inverted classroom, science education

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Authors: Qian Yi Ooi

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At present, airfoil parameters are still designed and optimized according to the scale of conventional aircraft, and there are still some slight deviations in terms of scale differences. However, insufficient parameters or poor surface mesh quality is likely to occur if these small deviations are embedded in a future civil aircraft with a size that is quite different from conventional aircraft, such as a blended-wing-body (BWB) aircraft with future potential, resulting in large deviations in geometric similarity in computational fluid dynamics (CFD) simulations. To avoid this situation, the study on the CFD calculation on the geometric similarity of airfoil parameters and the quality of the surface mesh is conducted to obtain the ability of different parameterization methods applied on different airfoil scales. The research objects are three airfoil scales, including the wing root and wingtip of conventional civil aircraft and the wing root of the giant hybrid wing, used by three parameterization methods to compare the calculation differences between different sizes of airfoils. In this study, the constants including NACA 0012, a Reynolds number of 10 million, an angle of attack of zero, a C-grid for meshing, and the k-epsilon (k-ε) turbulence model are used. The experimental variables include three airfoil parameterization methods: point cloud method, B-spline curve method, and class function/shape function transformation (CST) method. The airfoil dimensions are set to 3.98 meters, 17.67 meters, and 48 meters, respectively. In addition, this study also uses different numbers of edge meshing and the same bias factor in the CFD simulation. Studies have shown that with the change of airfoil scales, different parameterization methods, the number of control points, and the meshing number of divisions should be used to improve the accuracy of the aerodynamic performance of the wing. When the airfoil ratio increases, the most basic point cloud parameterization method will require more and larger data to support the accuracy of the airfoil’s aerodynamic performance, which will face the severe test of insufficient computer capacity. On the other hand, when using the B-spline curve method, average number of control points and meshing number of divisions should be set appropriately to obtain higher accuracy; however, the quantitative balance cannot be directly defined, but the decisions should be made repeatedly by adding and subtracting. Lastly, when using the CST method, it is found that limited control points are enough to accurately parameterize the larger-sized wing; a higher degree of accuracy and stability can be obtained by using a lower-performance computer.

Keywords: airfoil, computational fluid dynamics, geometric similarity, surface mesh quality

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Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke

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The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.

Keywords: generalized autoregressive score model, South Africa, stock returns, time-varying

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Authors: D. Zhigulskaya, V. Anisimov, A. Pikunov, K. Babanova, S. Zuev, A. Latyshkova, K. Сhernozatonskiy, A. Revazov

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Electrophysiology of information processing in reading is certainly a popular research topic. Natural reading, however, has been relatively poorly studied, despite having broad potential applications for learning and education. In the current study, we explore the relationship between text categories and spontaneous electroencephalogram (EEG) while reading. Thirty healthy volunteers (mean age 26,68 ± 1,84) participated in this study. 15 Russian-language texts were used as stimuli. The first text was used for practice and was excluded from the final analysis. The remaining 14 were opposite pairs of texts in one of 7 categories, the most important of which were: interesting/boring, fiction/non-fiction, free reading/reading with an instruction, reading a text/reading a pseudo text (consisting of strings of letters that formed meaningless words). Participants had to read the texts sequentially on an Apple iPad Pro. EEG was recorded from 12 electrodes simultaneously with eye movement data via ARKit Technology by Apple. EEG spectral amplitude was analyzed in Fz for theta-band (4-8 Hz) and in C3, C4, P3, and P4 for alpha-band (8-14 Hz) using the Friedman test. We found that reading an interesting text was accompanied by an increase in theta spectral amplitude in Fz compared to reading a boring text (3,87 µV ± 0,12 and 3,67 µV ± 0,11, respectively). When instructions are given for reading, we see less alpha activity than during free reading of the same text (3,34 µV ± 0,20 and 3,73 µV ± 0,28, respectively, for C4 as the most representative channel). The non-fiction text elicited less activity in the alpha band (C4: 3,60 µV ± 0,25) than the fiction text (C4: 3,66 µV ± 0,26). A significant difference in alpha spectral amplitude was also observed between the regular text (C4: 3,64 µV ± 0,29) and the pseudo text (C4: 3,38 µV ± 0,22). These results suggest that some brain activity we see on EEG is sensitive to particular features of the text. We propose that changes in theta and alpha bands during reading may serve as electrophysiological tools for assessing the reader’s cognitive state as well as his or her attitude to the text and the perceived information. These physiological markers have prospective practical value for developing technological solutions and biofeedback systems for reading in particular and for education in general.

Keywords: EEG, natural reading, reader's cognitive state, theta-rhythm, alpha-rhythm

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Authors: Abdur Rosyid, Mohamed El-Madany, Mohanad Alata

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Due to simplicity and low cost, rotordynamic system is often modeled by using lumped parameters. Recently, finite elements have been used to model rotordynamic system as it offers higher accuracy. However, it involves high degrees of freedom. In some applications such as control design, this requires higher cost. For this reason, various model reduction methods have been proposed. This work demonstrates the quality of model reduction of rotor-bearing-support system through substructuring. The quality of the model reduction is evaluated by comparing some first natural frequencies, modal damping ratio, critical speeds and response of both the full system and the reduced system. The simulation shows that the substructuring is proven adequate to reduce finite element rotor model in the frequency range of interest as long as the numbers and the locations of master nodes are determined appropriately. However, the reduction is less accurate in an unstable or nearly-unstable system.

Keywords: rotordynamic, finite element model, timoshenko beam, 3D solid elements, Guyan reduction method

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Authors: Aakash Chhunchha, Assma Begum

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The qualitative aspects of hypersonic flow over a range of blunt bodies have been extensively analyzed in the past. It is well known that the curvature of a body’s geometry in the sonic region predominantly dictates the bow shock shape and its standoff distance from the body, while the surface pressure distribution depends on both the sonic region and on the local body shape. The present study is an extension to analyze the hypersonic flow characteristics over several blunt-nosed bodies using modern Computational Fluid Dynamics (CFD) tools to determine the shock shape and its effect on the heat flux around the body. 4 blunt-nosed models with cylindrical afterbodies were analyzed for a flow at a Mach number of 10 corresponding to the standard atmospheric conditions at an altitude of 50 km. The nose radii of curvature of the models range from a hemispherical nose to a flat nose. Appropriate numerical models and the supplementary convergence techniques that were implemented for the CFD analysis are thoroughly described. The flow contours are presented highlighting the key characteristics of shock wave shape, shock standoff distance and the sonic point shift on the shock. The variation of heat flux, due to different shock detachments for various models is comprehensively discussed. It is observed that the more the bluntness of the nose radii, the farther the shock stands from the body; and consequently, the less the surface heating at the nose. The results obtained from the CFD analyses are compared with approximated theoretical engineering correlations. Overall, a satisfactory agreement is observed between the two.

Keywords: aero-thermodynamics, blunt-nosed bodies, computational fluid dynamics (CFD), hypersonic flow

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Authors: N. Naga Subrahmanyeswara Rao, Parag Arvind Deshpande

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Understanding nucleotide synthesis reaction of any organism is beneficial to know the growth of it as in Mycobacterium tuberculosis to design anti TB drug. One of the reactions of de novo pathway which takes place in all organisms was considered. The reaction takes places between phosphoribosyl pyrophosphate and orotate catalyzed by orotate phosphoribosyl transferase and divalent metal ion gives orotdine monophosphate, a nucleotide. All the reaction steps of three experimentally proposed mechanisms for this reaction were considered to develop kinetic rate expression. The model was validated using the data for four organisms. This model could successfully describe the kinetics for the reported data. The developed model can serve as a reliable model to describe the kinetics in new organisms without the need of mechanistic determination. So an organism-independent model was developed.

Keywords: mechanism, nucleotide, organism, tuberculosis

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Authors: C. Cohen, O. Levi

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This work introduces a generalization of the classical Tullock’s model of one-stage contests under complete information with multiple unlimited numbers of contestants. In classical Tullock’s model, the contest winner is not necessarily the highest bidder. Instead, the winner is determined according to a draw in which the winning probabilities are the relative contestants’ efforts. The Tullock modeling fits well political contests, in which the winner is not necessarily the highest effort contestant. This work presents a modified model which uses a simple non-discriminating rule, namely, a parameter to influence the total costs planned for an election, for example, the contest designer can control the contestants' efforts. The winner pays a fee, and the losers are reimbursed the same amount. Our proposed model includes a mechanism that controls the efforts exerted and balances competition, creating a tighter, less predictable and more interesting contest. Additionally, the proposed model follows the fairness criterion in the sense that it does not alter the contestants' probabilities of winning compared to the classic Tullock’s model. We provide an analytic solution for the contestant's optimal effort and expected reward.

Keywords: contests, Tullock's model, political elections, control expenses

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Authors: Michelle V. Tomczak, Reyhaneh Bakhtiari, Aaron Granley, Anthony Singhal

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Objective: Cannabis and cocaine are associated with a range of mental and physical effects that can impair aspects of human behavior. Driving is a complex cognitive behavior that is an essential part of everyday life and can be broken down into many subcomponents, each of which can uniquely impact road safety. With the growing movement of jurisdictions to legalize cannabis, there is an increased focus on impairment and driving. The purpose of this study was to identify driving-related cognitive-performance deficits that are impacted by recreational drug use. Design and Methods: With the assistance of law enforcement agencies, we recruited over 300 participants under the influence of various drugs including cannabis and cocaine. These individuals performed a battery of computer-based tasks scientifically proven to be re-lated to on-road driving performance and designed to test response-speed, memory processes, perceptual-motor skills, and decision making. Data from a control group with healthy non-drug using adults was collected as well. Results: Compared to controls, the drug group showed def-icits in all tasks. The data also showed clear differences between the cannabis and cocaine groups where cannabis users were faster, and performed better on some aspects of the decision-making and perceptual-motor tasks. Memory performance was better in the cocaine group for simple tasks but not more complex tasks. Finally, the participants who consumed both drugs performed most similarly to the cannabis group. Conclusions: Our results show distinct and combined effects of cannabis and cocaine on human performance relating to driving. These dif-ferential effects are likely related to the unique effects of each drug on the human brain and how they distinctly contribute to mental states. Our results have important implications for road safety associated with driver impairment.

Keywords: driving, cognitive impairment, recreational drug use, cannabis and cocaine

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Authors: Deeksha Arora

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The study aims to explore the applicability of the widely used asset pricing models, namely, Capital Asset Pricing Model (CAPM) and the Fama-French Four Factor Model in the Indian equity market. The study will be based on the companies that form part of the Nifty Fifty Index for a period of five years: 2011 to 2016. The asset pricing model is examined by forming portfolios on the basis of three variables – market capitalization (size effect), book-to-market equity ratio (value effect) and profitability. The study provides a basis to test the presence of the Fama-French Four factor model in Indian stock market. This study may provide a basis for future research in the generalized asset pricing model comprising of multiple risk factors.

Keywords: book to market equity, Fama French four factor model, market capitalization, profitability, size effect, value effect

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Authors: Abdellahi Cheikh

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With the emergence of quantum computers with very powerful capabilities, the security of the exchange of shared keys between two interlocutors poses a big problem in terms of the rapid development of technologies such as computing power and computing speed. Therefore, the Diffie-Hellmann (DH) algorithm is more vulnerable than ever. No mechanism guarantees the security of the key exchange, so if an intermediary manages to intercept it, it is easy to intercept. In this regard, several studies have been conducted to improve the security of key exchange between two interlocutors, which has led to interesting results. The modification made on our model Diffie-Hellman-RSA-AES (DRA), which encrypts the information exchanged between two users using the three-encryption algorithms DH, RSA and AES, by using stenographic photos to hide the contents of the p, g and ClesAES values that are sent in an unencrypted state at the level of DRA model to calculate each user's public key. This work includes a comparative study between the DRA model and all existing solutions, as well as the modification made to this model, with an emphasis on the aspect of reliability in terms of security. This study presents a simulation to demonstrate the effectiveness of the modification made to the DRA model. The obtained results show that our model has a security advantage over the existing solution, so we made these changes to reinforce the security of the DRA model.

Keywords: Diffie-Hellmann, DRA, RSA, advanced encryption standard

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Authors: O. Afshar

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Unlike other renewable energy sources, tidal current energy is an extremely reliable, predictable and continuous energy source as the current pattern and speed can be predicted throughout the year. A key concern associated with tidal turbines is their long-term reliability when operating in the hostile marine environment. Bio-fouling changes the physical shape and roughness of turbine components, hence altering the overall turbine performance. This paper seeks to employ Computational Fluid Dynamics (CFD) method to quantify the effects of this problem based on the obtained flow field information. The simulation is carried out on a NACA 63-618 aerofoil. The Reynolds Averaged Navier-Stokes (RANS) equations with Shear Stress Transport (SST) turbulent model are used to simulate the flow around the model. Different levels of fouling are studied on 2D aerofoil surface with quantified fouling height and density. In terms of lift and drag coefficient results, numerical results show good agreement with the experiment which was carried out in wind tunnel. Numerical results of research indicate that an increase in fouling thickness causes an increase in drag coefficient and a reduction in lift coefficient. Moreover, pressure gradient gradually becomes adverse as height of fouling increases. In addition, result by turbulent kinetic energy contour reveals it increases with fouling height and it extends into wake due to flow separation.

Keywords: tidal energy, lift coefficient, drag coefficient, roughness

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history seismic analysis is supposed to be the most accurate method to predict the seismic demand of structures. On the other hand, the required computational time of this method toward achieving the result is its main deficiency. While being applied in optimization process, in which the structure must be analyzed thousands of time, reducing the required computational time of seismic analysis of structures makes the optimization algorithms more practical. Apparently, the invented approximate methods produce some amount of errors in comparison with exact time history analysis but the recently proposed method namely, Complete Quadratic Combination (CQC) and Sum Root of the Sum of Squares (SRSS) drastically reduces the computational time by combination of peak responses in each mode. In the present research, the Basic Modal Displacement (BMD) method is introduced and applied towards estimation of seismic demand of main structure. Seismic demand of sampled structure is estimated by calculation of modal displacement of basic structure (in which the modal displacement has been calculated). Shear steel sampled structures are selected as case studies. The error applying the introduced method is calculated by comparison of the estimated seismic demands with exact time history dynamic analysis. The efficiency of the proposed method is demonstrated by application of three types of earthquakes (in view of time of peak ground acceleration).

Keywords: time history dynamic analysis, basic modal displacement, earthquake-induced demands, shear steel structures

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Authors: Manoja Rajalakshmi Aravindakshana, Devleena Ghosha, Chittaranjan Mandala, K. V. Venkateshb, Jit Sarkarc, Partha Chakrabartic, Sujay K. Maity

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Oral Glucose Tolerance Test (OGTT) is the primary test used to diagnose type 2 diabetes mellitus (T2DM) in a clinical setting. Analysis of OGTT data using the Oral Minimal Model (OMM) along with the rate of appearance of ingested glucose (Ra) is performed to study differences in model parameters for control and T2DM groups. The differentiation of parameters of the model gives insight into the behaviour and physiology of T2DM. The model is also studied to find parameter differences among obese and non-obese T2DM subjects and the sensitive parameters were co-related to the known physiological findings. Sensitivity analysis is performed to understand changes in parameter values with model output and to support the findings, appropriate statistical tests are done. This seems to be the first preliminary application of the OMM with obesity as a distinguishing factor in understanding T2DM from estimated parameters of insulin-glucose model and relating the statistical differences in parameters to diabetes pathophysiology.

Keywords: oral minimal model, OGTT, obese and non-obese T2DM, mathematical modeling, parameter estimation

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Authors: Liliana Villavicencio, Yohn Garcia, Pallavi Singh, Luis Fernando Cruz, Wilfrido Moreno

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Psychophysiological adaptive automation is a concept that combines human physiological data and computer algorithms to create personalized interfaces and experiences for users. This approach aims to enhance human learning by adapting to individual needs and preferences and optimizing the interaction between humans and machines. According to neurosciences, the working memory demand during the student learning process is modified when the student is learning a new subject or topic, managing and/or fulfilling a specific task goal. A sudden increase in working memory demand modifies the level of students’ attention, engagement, and cognitive load. The proposed psychophysiological adaptive automation system will adapt the task requirements to optimize cognitive load, the process output variable, by monitoring the student's brain activity. Cognitive load changes according to the student’s previous knowledge, the type of task, the difficulty level of the task, and the overall psychophysiological state of the student. Scaling the measured cognitive load as low, medium, or high; the system will assign a task difficulty level to the next task according to the ratio between the previous-task difficulty level and student stress. For instance, if a student becomes stressed or overwhelmed during a particular task, the system detects this through signal measurements such as brain waves, heart rate variability, or any other psychophysiological variables analyzed to adjust the task difficulty level. The control of engagement and stress are considered internal variables for the hypermedia system which selects between three different types of instructional material. This work assesses the feasibility of a fuzzy controller to track a student's physiological responses and adjust the learning content and pace accordingly. Using an industrial automation approach, the proposed fuzzy logic controller is based on linguistic rules that complement the instrumentation of the system to monitor and control the delivery of instructional material to the students. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the delivery of academic content based on the working memory demand without compromising students’ health. This work has a potential application in the instructional design of virtual reality environments for training and education.

Keywords: fuzzy logic controller, hypermedia control system, personalized education, psychophysiological adaptive automation

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Authors: Khaled Salah

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Model order reduction has been one of the most challenging topics in the past years. In this paper, a hybrid solution of genetic algorithm (GA) and simulated annealing algorithm (SA) are used to approximate high-order transfer functions (TFs) to lower-order TFs. In this approach, hybrid algorithm is applied to model order reduction putting in consideration improving accuracy and preserving the properties of the original model which are two important issues for improving the performance of simulation and computation and maintaining the behavior of the original complex models being reduced. Compared to conventional mathematical methods that have been used to obtain a reduced order model of high order complex models, our proposed method provides better results in terms of reducing run-time. Thus, the proposed technique could be used in electronic design automation (EDA) tools.

Keywords: genetic algorithm, simulated annealing, model reduction, transfer function

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Authors: Simran Sharda

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There is increasing evidence that leads psychologists today to believe that the attachment formed between a mother and child plays a much more profound role in later-life outcomes than previously expected. Particularly, the fact that a link may exist between maternal attachment and the development in addition to the severity of social anxiety in middle childhood seems to be gaining ground. This research will examine and address a myriad of major issues related to the impact of mother-child attachment: behaviors of children with different levels of secure attachment, various aspects of anxiety in relation to attachment security as well as other styles of mother-child attachments, especially avoidant attachment and over-attachment. This analysis serves to compile previous literature on the subject and touch light upon a logical extension of the research. Moreover, researchers have identified links between attachment and the externalization of problem behaviors: these behaviors may later manifest as social anxiety as well as increased severity and likelihood of PTSD diagnosis (an anxiety disorder). Furthermore, secure attachment has been linked to increased health benefits, cognitive skills, emotive socialization, and developmental psychopathology.

Keywords: child development, anxiety, cognition, developmental psychopathology, mother-child relationships, maternal, cognitive development

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Authors: C. D. Ellis, H. Xia, X. Chen

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Experimental and computational studies investigating heat transfer in separated flows have been of increasing importance over the last 60 years, as efforts are being made to understand and improve the efficiency of components such as combustors, turbines, heat exchangers, nuclear reactors and cooling channels. Understanding of not only the time-mean heat transfer properties but also the unsteady properties is vital for design of these components. As computational power increases, more sophisticated methods of modelling these flows become available for use. The hybrid LES-RANS approach has been applied to a blunt leading edge flat plate, utilising a structured grid at a moderate Reynolds number of 20300 based on the plate thickness. In the region close to the wall, the RANS method is implemented for two turbulence models; the one equation Spalart-Allmaras model and Menter’s two equation SST k-ω model. The LES region occupies the flow away from the wall and is formulated without any explicit subgrid scale LES modelling. Hybridisation is achieved between the two methods by the blending of the nearest wall distance. Validation of the flow was obtained by assessing the mean velocity profiles in comparison to similar studies. Identifying the vortex structures of the flow was obtained by utilising the λ2 criterion to identify vortex cores. The qualitative structure of the flow compared with experiments of similar Reynolds number. This identified the 2D roll up of the shear layer, breaking down via the Kelvin-Helmholtz instability. Through this instability the flow progressed into hairpin like structures, elongating as they advanced downstream. Proper Orthogonal Decomposition (POD) analysis has been performed on the full flow field and upon the surface temperature of the plate. As expected, the breakdown of POD modes for the full field revealed a relatively slow decay compared to the surface temperature field. Both POD fields identified the most energetic fluctuations occurred in the separated and recirculation region of the flow. Latter modes of the surface temperature identified these levels of fluctuations to dominate the time-mean region of maximum heat transfer and flow reattachment. In addition to the current research, work will be conducted in tracking the movement of the vortex cores and the location and magnitude of temperature hot spots upon the plate. This information will support the POD and statistical analysis performed to further identify qualitative relationships between the vortex dynamics and the response of the surface heat transfer.

Keywords: heat transfer, hybrid LES-RANS, separated and reattached flow, vortex dynamics

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Authors: Mohamed Roudane

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The objective of this study is to know the dynamic behavior of a multi swirling jet used for air conditioning inside a room. To conduct this study, we designed a facility to ensure proper conditions of confinement in which we placed five air blowing devices with adjustable vanes, providing multiple swirling turbulent jets. The jets were issued in the same direction and the same spacing defined between them. This study concerned the numerical simulation of the dynamic mixing of confined swirling multi-jets, and examined the influence of important parameters of a swirl diffuser system on the dynamic performance characteristics. The CFD investigations are carried out by a hybrid mesh to discretize the computational domain. In this work, the simulations have been performed using the finite volume method and FLUENT solver, in which the standard k-ε RNG turbulence model was used for turbulence computations.

Keywords: simulation, dynamic behavior, swirl, turbulent jet

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: Mesbah Khaled, Bouraoui Ouissal, Benkiniouar Rachid, Belkhiri Lotfi

Abstract:

Alstonia, which are tropical plants with a wide geographical distribution, have been divided into different sections by different authors based on previous studies of several species within the genus. Monachino divides Alstonia into 5 sections, while Pichon divides it into 3 sections. Several plants belonging to this genus, such as Alstonia brassii, have been used in traditional folk medicine to treat ailments such as fever, malaria and dysentery]. Previous studies focusing on the chemical composition of these plants have successfully identified indol alkaloids with cytotoxic, anti-diabetic and anti-inflammatory properties. The newly discovered monomers are structurally similar to the backbones of picralin, affinisin and macrolin. On the other hand, all recently isolated dimeric compounds have a macrolin moiety. In this study, a computational analysis was performed on a series of novel molecules, including both monomeric and dimeric compounds with different structural frameworks. This investigation represents the first computational study of these molecules using an in silico approach incorporating 2D-QSAR data. The analysis involved various computational techniques, including 2D-QSAR modelling, molecular docking studies and subsequent validation by molecular dynamics simulation and assessment of ADMET properties. The chemical composition was identified by 1D and 2D NMR. Eight new alkaloids were isolated, 5 monomers and 3 dimers. In this section, we focus on the biological activity of 4 new alkaloids belonging to two different skeletons, the affinisine skeleton.

Keywords: affinisine, talcarpine, macroline, cytotoxicity, alkaloids

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Authors: Jessemyn Modiini, Timothy Lynar, Elena Sitnikova

Abstract:

We present a novel enhanced compartmental model for malware spread analysis in cyber security. This paper applies cyber security data features to epidemiological compartmental models to model the infectious potential of malware. Compartmental models are most efficient for calculating the infectious potential of a disease. In this paper, we discuss and profile epidemiologically relevant data features from a Domain Name System (DNS) dataset. We then apply these features to epidemiological compartmental models to network traffic features. This paper demonstrates how epidemiological principles can be applied to the novel analysis of key cybersecurity behaviours and trends and provides insight into threat modelling above that of kill-chain analysis. In applying deterministic compartmental models to a cyber security use case, the authors analyse the deficiencies and provide an enhanced stochastic model for cyber epidemiology. This enhanced compartmental model (SUEICRN model) is contrasted with the traditional SEIR model to demonstrate its efficacy.

Keywords: cybersecurity, epidemiology, cyber epidemiology, malware

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Authors: Gamal Abd El-Nasser A. Said, El-Sayed M. El-Horbaty

Abstract:

Container handling problems at container terminals are NP-hard problems. This paper presents an approach using discrete-event simulation modeling to optimize solution for storage space allocation problem, taking into account all various interrelated container terminal handling activities. The proposed approach is applied on a real case study data of container terminal at Alexandria port. The computational results show the effectiveness of the proposed model for optimization of storage space allocation in container terminal where 54% reduction in containers handling time in port is achieved.

Keywords: container terminal, discrete-event simulation, optimization, storage space allocation

Procedia PDF Downloads 326

Authors: K. Aravinth, C. T. Vignesh

Abstract:

The usage of pulse tube cryocoolers is significantly increased mainly due to the advantage of the absence of moving parts. The underlying idea of this project is to optimize the design of pulse tube, regenerator, a resonator in cryocooler and analyzing the thermo-acoustic oscillations with respect to the design parameters. Computational Fluid Dynamic (CFD) model with time-dependent validation is done to predict its performance. The continuity, momentum, and energy equations are solved for various porous media regions. The effect of changing the geometries and orientation will be validated and investigated in performance. The pressure, temperature and velocity fields in the regenerator and pulse tube are evaluated. This optimized design performance results will be compared with the existing pulse tube cryocooler design. The sinusoidal behavior of cryocooler in acoustic streaming patterns in pulse tube cryocooler will also be evaluated.

Keywords: acoustics, cryogenics, design, optimization

Procedia PDF Downloads 175

Authors: Eko Liao, Cheryl Zhang

Abstract:

Employee job crafting refers to employee’s proactive behaviors of making customized changes to their jobs on cognitive, relationship, and task levels. Previous studies have investigated different situations triggering employee’s job crafting. However, much less is known about what would be the consequences for both employee themselves and their work groups. Guided by conservation of resources theory (COR), this study investigates how employees job crafting increases their objective task performance and promotive voice behaviors at work. It is argued that employee would gain more resources when they actively craft their job tasks, which in turn increase their job performance and encourage them to have more constructive speak-up behaviors. Specifically, employee’s psychological resources (i.e., job engagement) and relational resources (i.e., leader-member relationships) would be enhanced from effective crafting behaviors, because employees are more likely to regard their job tasks as meaningful, and their leaders would be more likely to notice and recognize their dedication at work when employees craft their job frequently. To test this research model, around 400 employees from various Chinese organizations from mainland China joins the two-wave data collection stage. Employee’s job crafting behaviors in three aspects are measured at time 1. Perception of resource gain (job engagement and leader-member exchange), voice, and job performance are measured at time 2. The research model is generally supported. This study contributes to the job crafting literature by broadening the theoretical lens to a resource-based perspective. It also has practical implications that organizations should pay more attention to employee crafting behaviors because they are closely related to employees in-role performance and constructive voice behaviors.

Keywords: job crafting, resource-based perspective, voice, job performance

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Authors: V. Keim, J. Spachtholz, J. Hammer

Abstract:

The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation

Procedia PDF Downloads 215

Authors: Rafid A. Al-Khannak, Fawzi M. Al-Naima

Abstract:

Power load is one of the most important controlling keys which decide power demands and illustrate power usage to shape power market. Hence, power load forecasting is the parameter which facilitates understanding and analyzing all these aspects. In this paper, power load forecasting is solved under MATLAB environment by constructing a neural network for the power load to find an accurate simulated solution with the minimum error. A developed algorithm to achieve load forecasting application with faster technique is the aim for this paper. The algorithm is used to enable MATLAB power application to be implemented by multi machines in the Grid computing system, and to accomplish it within much less time, cost and with high accuracy and quality. Grid Computing, the modern computational distributing technology, has been used to enhance the performance of power applications by utilizing idle and desired Grid contributor(s) by sharing computational power resources.

Keywords: DeskGrid, Grid Server, idle contributor(s), grid computing, load forecasting

Procedia PDF Downloads 476