Search results for: integrative model of behavior prediction

Authors: Chui Ka Shing

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This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed.

Keywords: bar model method, curriculum development, mathematics education, problem solving

Procedia PDF Downloads 220

Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: Antoinette Maarawi, Zoe Anxionnaz-Minvielle, Pierre Coste, Nathalie Di Miceli Raimondi, Michel Cabassud

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Milli-structured heat exchanger/reactors have been recently widely used, especially in the chemical industry, due to their enhanced performances in heat and mass transfer compared to conventional apparatuses. In our work, the ‘DeanHex’ heat exchanger/reactor with a 2D-meandering channel is investigated both experimentally and numerically. The square cross-sectioned channel has a hydraulic diameter of 2mm. The aim of our study is to model local physico-chemical phenomena (heat and mass transfer, axial dispersion, etc.) for a liquid-liquid two-phase flow in our lab-scale meandering channel, which represents the central part of the heat exchanger/reactor design. The numerical approach of the reactor is based on a 1D model for the flow channel encapsulated in a 3D model for the surrounding solid, using COMSOL Multiphysics V5.5. The use of the 1D approach to model the milli-channel reduces significantly the calculation time compared to 3D approaches, which are generally focused on local effects. Our 1D/3D approach intends to bridge the gap between the simulation at a small scale and the simulation at the reactor scale at a reasonable CPU cost. The heat transfer process between the 1D milli-channel and its 3D surrounding is modeled. The feasibility of this 1D/3D coupling was verified by comparing simulation results to experimental ones originated from two previous works. Temperature profiles along the channel axis obtained by simulation fit the experimental profiles for both cases. The next step is to integrate the liquid-liquid mass transfer model and to validate it with our experimental results. The hydrodynamics of the liquid-liquid two-phase system is modeled using the ‘mixture model approach’. The mass transfer behavior is represented by an overall volumetric mass transfer coefficient ‘kLa’ correlation obtained from our experimental results in the millimetric size meandering channel. The present work is a first step towards the scale-up of our ‘DeanHex’ expecting future industrialization of such equipment. Therefore, a generalized scaled-up model of the reactor comprising all the transfer processes will be built in order to predict the performance of the reactor in terms of conversion rate and energy efficiency at an industrial scale.

Keywords: liquid-liquid mass transfer, milli-structured reactor, 1D/3D model, process intensification

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Authors: Ehsan Sadie

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The use of steel braces in concrete structures has been considered by researchers in recent decades due to its easy implementation, economics and the ability to create skylights in braced openings compared to shear wall openings as well as strengthening weak concrete structures to earthquakes. The purpose of this article is to improve and strengthen concrete structures with steel bracing. In addition, cases such as different numbers of steel braces in different openings of concrete structures and interaction between concrete frames and metal braces have been studied. In this paper, by performing static nonlinear analysis and examining ductility, the relative displacement of floors, examining the performance of samples, and determining the coefficient of behavior of composite frames (concrete frames with metal bracing), the behavior of reinforced concrete frames is compared with frame without bracing. The results of analyzes and studies show that the addition of metal bracing increases the strength and stiffness of the frame and reduces the ductility and lateral displacement of the structure. In general, the behavior of the structure against earthquakes will be improved.

Keywords: behavior coefficient, bracing, concrete structure, convergent bracing, earthquake, linear static analysis, nonlinear analysis, pushover curve

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Authors: Moustafa Osman

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Modeling of air pollutants from the accidental release is performed for quantifying the impact of industrial facilities into the ambient air. The mathematical methods are requiring for the prediction of the accidental scenario in probability of failure-safe mode and analysis consequences to quantify the environmental damage upon human health. The initial statement of mitigation plan is supporting implementation during production and maintenance periods. In a number of mathematical methods, the flow rate at which gaseous and liquid pollutants might be accidentally released is determined from various types in term of point, line and area sources. These emissions are integrated meteorological conditions in simplified stability parameters to compare dispersion coefficients from non-continuous air pollution plumes. The differences are reflected in concentrations levels and greenhouse effect to transport the parcel load in both urban and rural areas. This research reveals that the elevation effect nearby buildings with other structure is higher 5 times more than open terrains. These results are agreed with Sutton suggestion for dispersion coefficients in different stability classes.

Keywords: air pollutants, dispersion modeling, GIS, health effect, urban planning

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Authors: Mehdi Ghatei, Masoomeh Lorestani

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Upstream Tailings Storage Facilities (TSFs) may experience slope instabilities due to soil liquefaction, especially in regions known to be seismically active. In this study, liquefaction susceptibility of an upstream-raised TSF in Western Australia was assessed using two different approaches. The first approach assessed liquefaction susceptibility using Cone Penetration Tests with pore pressure measurement (CPTu) as described by the National Centre for Earthquake Engineering Research (NCEER). This assessment was based on the four CPTu tests that were conducted on the perimeter embankment of the TSF. The second approach used the Finite Element (FE) method with application of an equivalent linear model to predict the undrained cyclic behavior, the pore water pressure and the liquefaction of the materials. The tailings parameters were estimated from the CPTu profiles and from the laboratory tests. The cyclic parameters were estimated from the literature where test results of similar material were available. The results showed that there was a good agreement, in the liquefaction susceptibility of the tailings material, between the NCEER and FE methods with equivalent linear model.

Keywords: liquefaction , CPTU, NCEER, finite element method, equivalent linear model

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

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Authors: Jerome Joshi

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The paper presents the modelling of financial markets using the Stochastic Pi Calculus model. The Stochastic Pi Calculus model is mainly used for biological applications; however, the feature of this model promotes its use in financial markets, more prominently in high frequency trading. The trading system can be broadly classified into exchange, market makers or intermediary traders and fundamental traders. The exchange is where the action of the trade is executed, and the two types of traders act as market participants in the exchange. High frequency trading, with its complex networks and numerous market participants (intermediary and fundamental traders) poses a difficulty while modelling. It involves the participants to seek the advantage of complex trading algorithms and high execution speeds to carry out large volumes of trades. To earn profits from each trade, the trader must be at the top of the order book quite frequently by executing or processing multiple trades simultaneously. This would require highly automated systems as well as the right sentiment to outperform other traders. However, always being at the top of the book is also not best for the trader, since it was the reason for the outbreak of the ‘Hot – Potato Effect,’ which in turn demands for a better and more efficient model. The characteristics of the model should be such that it should be flexible and have diverse applications. Therefore, a model which has its application in a similar field characterized by such difficulty should be chosen. It should also be flexible in its simulation so that it can be further extended and adapted for future research as well as be equipped with certain tools so that it can be perfectly used in the field of finance. In this case, the Stochastic Pi Calculus model seems to be an ideal fit for financial applications, owing to its expertise in the field of biology. It is an extension of the original Pi Calculus model and acts as a solution and an alternative to the previously flawed algorithm, provided the application of this model is further extended. This model would focus on solving the problem which led to the ‘Flash Crash’ which is the ‘Hot –Potato Effect.’ The model consists of small sub-systems, which can be integrated to form a large system. It is designed in way such that the behavior of ‘noise traders’ is considered as a random process or noise in the system. While modelling, to get a better understanding of the problem, a broader picture is taken into consideration with the trader, the system, and the market participants. The paper goes on to explain trading in exchanges, types of traders, high frequency trading, ‘Flash Crash,’ ‘Hot-Potato Effect,’ evaluation of orders and time delay in further detail. For the future, there is a need to focus on the calibration of the module so that they would interact perfectly with other modules. This model, with its application extended, would provide a basis for researchers for further research in the field of finance and computing.

Keywords: concurrent computing, high frequency trading, financial markets, stochastic pi calculus

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Authors: Cristian Crespo

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Conditional cash transfers (CCTs) have been targeted towards the poor. Thus, their targeting assessments check whether these schemes have been allocated to low-income households or individuals. However, CCTs have more than one goal and target group. An additional goal of CCTs is to increase school enrolment. Hence, students at risk of dropping out of school also are a target group. This paper analyses whether one of the most common targeting mechanisms of CCTs, a proxy means test (PMT), is suitable to identify the poor and future school dropouts. The PMT is compared with alternative approaches that use the outputs of a predictive model of school dropout. This model was built using machine learning algorithms and rich administrative datasets from Chile. The paper shows that using machine learning outputs in conjunction with the PMT increases targeting effectiveness by identifying more students who are either poor or future dropouts. This joint targeting approach increases effectiveness in different scenarios except when the social valuation of the two target groups largely differs. In these cases, the most likely optimal approach is to solely adopt the targeting mechanism designed to find the highly valued group.

Keywords: conditional cash transfers, machine learning, poverty, proxy means tests, school dropout prediction, targeting

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents modeling of a Alternating Current (AC) Photovoltaic (PV) module using Matlab/Simulink. The proposed AC-PV module model is simple, realistic, and application oriented. The model is derived on module level as compared to cell level directly from the information provided by the manufacturer data sheet. DC-PV module, MPPT control, BC, VSI and LC filter, all were treated as a single unit. The model accounts for changes in variations of both irradiance and temperature. The AC-PV module proposed model is simulated and the results are compared with the datasheet projected numbers to validate model’s accuracy and effectiveness. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: PV modeling, AC PV Module, datasheet, VI curves irradiance, temperature, MPPT, Matlab/Simulink

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Authors: S. Ghafoori, A. Al-Harbi, B. Al-Ajmi, A. Al-Shaalan, A. Al-Ajmi, M. Ali Juma

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Seismic methods play an important role in the exploration for hydrocarbon reservoirs. However, the success of the method depends strongly on the reliability of the measured or predicted information regarding the velocity of sound in the media. Speed of sound has been used to study the thermodynamic properties of fluids. In this study, experimental data are reported and analyzed on the speed of sound in toluene and octane binary mixture. Three-factor three-level Box-Benhkam design is used to determine the significance of each factor, the synergetic effects of the factors, and the most significant factors on speed of sound. The developed mathematical model and statistical analysis provided a critical analysis of the simultaneous interactive effects of the independent variables indicating that the developed quadratic models were highly accurate and predictive.

Keywords: experimental design, octane, speed of sound, toluene

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Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

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When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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Authors: Xia Chen, Yulan Wang

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purpose: To compare the accuracy of Haigis, SRK/T, T2, Holladay 1, Hoffer Q, Barrett Universal II, Emmetropia Verifying Optical (EVO) and Kane for intraocular lens power calculation in patients with axial length (AL) ≥ 28 mm. Methods: In this retrospective single-center study, 50 eyes of 41 patients with AL ≥ 28 mm that underwent uneventful cataract surgery were enrolled. The actual postoperative refractive results were compared to the predicted refraction calculated with different formulas (Haigis, SRK/T, T2, Holladay 1, Hoffer Q, Barrett Universal II, EVO and Kane). The mean absolute prediction errors (MAE) 1 month postoperatively were compared. Results: The MAE of different formulas were as follows: Haigis (0.509), SRK/T (0.705), T2 (0.999), Holladay 1 (0.714), Hoffer Q (0.583), Barrett Universal II (0.552), EVO (0.463) and Kane (0.441). No significant difference was found among the different formulas (P = .122). The Kane and EVO formulas achieved the lowest level of mean prediction error (PE) and median absolute error (MedAE) (p < 0.05). Conclusion: The Kane and EVO formulas had a better success rate than others in predicting IOL power in high myopic eyes with AL longer than 28 mm in this study.

Keywords: cataract, power calculation formulas, intraocular lens, long axial length

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Authors: Puneet Katyal, Punit Kumar

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A great deal of efforts has been done in the field of thermal effects in electrohydrodynamic lubrication (TEHL) during the last five decades. The focus was primarily on the development of an efficient numerical scheme to deal with the computational challenges involved in the solution of TEHL model; however, some important aspects related to the accurate description of lubricant properties such as viscosity, rheology and thermal conductivity in EHL point contact analysis remain largely neglected. A few studies available in this regard are based upon highly complex mathematical models difficult to formulate and execute. Using a simplified thermal EHL model for point contacts, this work sheds some light on the importance of accurate characterization of the lubricant properties and demonstrates that the computed TEHL characteristics are highly sensitive to lubricant properties. It also emphasizes the use of appropriate mathematical models with experimentally determined parameters to account for correct lubricant behaviour.

Keywords: TEHL, shear thinning, rheology, conductivity

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Authors: Abdulsamee Halahla, Emad Allout

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The purpose of this research is to study the behavior of exterior beam-column joints (BCJs) strengthened with ultra-high performance concrete (UHPC), in terms of the shear strength and maximum displacement using pushover analysis at the tip of the beam. A finite element (F.E) analysis was performed to study three main parameters – the level of the axial load in the column (N), the beam shear reinforcement (Av/s)B, and the effect of using UHPC. The normal concrete at the studied joint region was replaced by UHPC. The model was verified by using experimental results taken from the literature. The results showed that the UHPC contributed to the transference of the plastic hinge from the joint to the beam-column interface. In addition, the strength of the UHPC-strengthened joints was enhanced dramatically from 8% to 38% for the joints subjected to 12.8MPa and zero axial loads, respectively. Moreover, the UHPC contributed in improving the maximum deflection. This improvement amounted to 1% and 176% for the joints subjected to zero and 12.8MPa axial load, respectively.

Keywords: ultra high performance concrete, ductility, reinforced concrete joints, finite element modeling, nonlinear behavior; pushover analysis

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Authors: Arista Mayang Sari Slamet

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This study was conducted to see the shape or behavior that shows the attitude of confidence in the practice of debate on science program students in Senior High School. This research is a descriptive qualitative study by explaining the forms of behavior of each indicator (there are ten indicators) confidence of Santrock. Data collection using interviews with Indonesian language teachers, direct observation, and documents. In this study, it was found that there is one item that is not visible indicator of the high school students of class X, which is the fourth item ‘Sitting with others in social activities’. This is caused by the forum examined are debating forum, so there is a social activity can’t be seen. The result of this study there are two students who do not show the behavior of confidence, their name is Dea and Audria (from the pro team). This indicates that the head of a pro team dominated the debate. The time for the debate is 45 minutes. Therefore all students in both of team can’t demonstrate their debate skill. In each team is only dominated by one student. The most common forms of confidence behavior are expressing opinion, look at the other person (speaker), and keeping eye contact with the other person. This indicates that the attitude of confidence by looking at the other person makes them more confident about their opinion. The most uncommon indicators is to direct or instruct to the other person. This shows that the attitude of self-confidence shown by the students isn’t lead.

Keywords: confidence, debate, senior high school, Jakarta

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Authors: Ulrike Dowie, Ralph Grothmann

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Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

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Authors: Catherine Maware, Olufemi Adetunji

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The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: impact measurement model, lean bundles, lean manufacturing, organizational performance

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Authors: Seok Hong Min, Tae Kwon Ha

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High-temperature deformation behavior of ferritic stainless steels such as STS 409L, STS 430J1L, and STS 429EM has been investigated in this study. Specimens with fully annealed microstructure were obtained by heat treatment. A series of load relaxation tests has been conducted on these samples at temperatures ranging from 200 to 900oC to construct flow curves in the strain rate range from 10-6 s-1 to 10-3 s-1. Strain hardening was not observed at high temperatures above 800oC in any stainless steels. Load relaxation behavior at the temperature was closely related with high-temperature mechanical properties such as the thermal fatigue and tensile behaviors. Load drop ratio of 436L stainless steel was much higher than that of the other steels. With increasing temperature, strength and load drop ratio of ferritic stainless steels showed entirely different trends.

Keywords: ferritic stainless steel, high temperature deformation, load relaxation, microstructure, strain rate sensitivity

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Authors: Hyungoo Kang, Minsung Kim, Jinkoo Kim

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This study investigates the performance of a 2D and 3D steel moment frame subjected to vehicle collision at a first story column using LS-DYNA. The finite element models of vehicles provided by the National Crash Analysis Center (NCAC) are used for numerical analysis. Nonlinear dynamic time history analysis of the 2D and 3D model structures are carried out based on the arbitrary column removal scenario, and the vertical displacement of the damaged structures are compared with that obtained from collision analysis. The analysis results show that the model structure remains stable when the speed of the vehicle is 40km/h. However, at the speed of 80 and 120km/h both the 2D and 3D structures collapse by progressive collapse. The vertical displacement of the damaged joint obtained from collision analysis is significantly larger than the displacement computed based on the arbitrary column removal scenario.

Keywords: vehicle collision, progressive collapse, FEM, LS-DYNA

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Authors: Thee Chowwanonthapunya, Junhua Dong, Wei Ke

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The atmospheres in many cities along the coastal lines in the world have been rapidly changed to coastal-industrial atmosphere. Hence, it is vital to investigate the corrosion behavior of steel exposed to this kind of environment. In this present study, Electrochemical Impedance Spectrography (EIS) and film thickness measurements were applied to monitor the corrosion behavior of weathering steel covered with a thin layer of the electrolyte in a wet-dry cyclic condition, simulating a coastal-industrial environment at 25 oC and 60 % RH. The results indicate that in all cycles, the corrosion rate increases during the drying process due to an increase in anion concentration and an acceleration of oxygen diffusion enhanced by the effect of the thinning out of the electrolyte. During the wet-dry cyclic corrosion test, the long-term corrosion behavior of this steel depends on the periods of exposure. Corrosion process is first accelerated and then decelerated. The decelerating corrosion process is contributed to the formation of the protective rust, favored by the wet-dry cycle and the acid regeneration process during the rusting process.

Keywords: atmospheric corrosion, EIS, low alloy, rust

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Authors: J. M. Lee, W. R. Noh, C. Y. Kim, M. G. Lee

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Delamination of oxide scale has been often discovered at the interface between Fe carbon steel and oxide scale. Among several mechanisms of this delamination behavior, the normal tensile stress to the substrate-scale interface has been described as one of the main factors. The stress distribution at the interface is also known to be affected by thermal expansion mismatch between substrate and oxide scale, creep behavior during cooling and the geometry of the interface. In this study, stress states near the interface in a Fe carbon steel with oxide scale have been investigated using FE simulations. The thermal and mechanical properties of oxide scales are indicated in literature and Fe carbon steel is measured using tensile testing machine. In particular, the normal and shear stress components developed at the interface during bending are investigated. Preliminary numerical sensitivity analyses are provided to explain the effects of the interface geometry and oxide thickness on the delamination behavior.

Keywords: oxide scale, delamination, Fe analysis, roughness, thickness, stress state

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Authors: R. Pilafkan, M. Kaffash Irzarahimi, S. F. Asbaghian Namin

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The biaxial buckling behavior of single-layered graphene sheets (SLGSs) is studied in the present work. To consider the size-effects in the analysis, Eringen’s nonlocal elasticity equations are incorporated into classical plate theory (CLPT). A Generalized Differential Quadrature Method (GDQM) approach is utilized and numerical solutions for the critical buckling loads are obtained. Then, molecular dynamics (MD) simulations are performed for a series of zigzag SLGSs with different side-lengths and with various boundary conditions, the results of which are matched with those obtained by the nonlocal plate model to numerical the appropriate values of nonlocal parameter relevant to each type of boundary conditions.

Keywords: biaxial buckling, single-layered graphene sheets, nonlocal elasticity, molecular dynamics simulation, classical plate theory

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Authors: Donald C. Lantu, Henndy Ginting, M. Yorga Permana, Dany M. A. Ramdlany

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We constructed a training program for top-talents of a Bank with Scharmer Theory-U as the model. In this training program, we implemented the action learning perspective, as it is claimed to be the most effective one currently available. In the process, participants were encouraged to be more involved, especially compared to traditional lecturing. The goal of this study is to assess the effectiveness of this particular training. The program consists of six days non-residential workshop within two months. Between each workshop, the participants were involved in the works of action learning group. They were challenged by dealing with the real problem related to their tasks at work. The participants of the program were 30 best talents who were chosen according to their yearly performance. Using paired difference statistical test in the behavioral assessment, we found that the training was not effective to increase participants’ leadership competencies. For the future development program, we suggested to modify the goals of the program toward the next stage of development.

Keywords: action learning, behavior, leadership development, Theory-U

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Authors: Ma Yuan, Zhang Mengxi, Akbar Javadi, Chen Longqing

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The structure of sand-filled embankment with cover layer is treated with tipping clay modified with lime on the outside of the packing, and the geotextile is placed between the stuffing and the clay. The packing is usually river sand, and the improved clay protects the sand core against rainwater erosion. The sand-filled embankment with cover layer has practical problems such as high filling embankment, construction restriction, and steep slope. The reinforcement can be applied to the sand-filled embankment with cover layer to solve the complicated problems such as irregular settlement caused by poor stability of the embankment. At present, the research on the sand-filled embankment with cover layer mainly focuses on the sand properties, construction technology, and slope stability, and there are few studies in the experimental field, the deformation characteristics and stability of reinforced sand-filled embankment need further study. In addition, experimental research is relatively rare when the cyclic load is considered in tests. A subgrade structure of geogrid-reinforced sand-filled embankment with cover layer was proposed. The mechanical characteristics, the deformation properties, reinforced behavior and the ultimate bearing capacity of the embankment structure under cyclic loading were studied. For this structure, the geogrids in the sand and the tipping soil are through the geotextile which is arranged in sections continuously so that the geogrids can cross horizontally. Then, the Unsaturated/saturated Soil Triaxial Test System of Geotechnical Consulting and Testing Systems (GCTS), USA was modified to form the loading device of this test, and strain collector was used to measuring deformation and earth pressure of the embankment. A series of cyclic loading model tests were conducted on the geogrid-reinforced sand-filled embankment with a cover layer under a different number of reinforcement layers, the length of reinforcement and thickness of the cover layer. The settlement of the embankment, the normal cumulative deformation of the slope and the earth pressure were studied under different conditions. Besides cyclic loading model tests, model experiments of embankment subjected cyclic-static loading was carried out to analyze ultimate bearing capacity with different loading. The experiment results showed that the vertical cumulative settlement under long-term cyclic loading increases with the decrease of the number of reinforcement layers, length of the reinforcement arrangement and thickness of the tipping soil. Meanwhile, these three factors also have an influence on the decrease of the normal deformation of the embankment slope. The earth pressure around the loading point is significantly affected by putting geogrid in a model embankment. After cyclic loading, the decline of ultimate bearing capacity of the reinforced embankment can be effectively reduced, which is contrary to the unreinforced embankment.

Keywords: cyclic load; geogrid; reinforcement behavior; cumulative deformation; earth pressure

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Authors: Howard Gomwe, Eunice Seekoe, Philemon Lyoka, Chioneso Show Marange, Dennyford Mafa

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Background: This study was designed to assess PA levels and sedentary behavior among primary school learners in the Eastern Cape province of South Africa. Methods: A cross-sectional study was adopted to assess the patterns and levels of PA and sedentary behavior using the Physical Activity Questionnaire for Older Children (PAQ-C). Results: Using complete case analysis, 870 randomly selected participants (boys = 351 and girls = 519) aged 9 to 14 years were retained. The sample comprised of primary school learners, both boys and girls; aged 9-14 years old, who were randomly selected from rural, urban and peri-urban areas in the Eastern Cape Province of South Africa. Overly, the sample had a mean PAQ-C score of 2.33 ± 0.43. The mean of PA in boys was significantly higher (p = 0.003) in comparison with the girls. The 13 to 14 age group had a significantly higher PA level (p = 0.014). Learners from urban areas (n = 136; 77.3%) engaged more in sedentary behaviour as compared to those from rural areas (n = 252; 54.9%). Conclusion: The findings demonstrated low levels of PA and high engagement of sedentary behavior, which have negative implications on the health, growth and development of children. The study, therefore, recommends relevant stakeholders to implement interventions aimed to promote the increase in PA and reduction in sedentary behaviors for primary school learners in the Eastern Cape province in South Africa.

Keywords: learners, physical activity, sedentary behavior, south Africa

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Authors: T. Sahbani, M. Bouteraa, R. Wamkeue

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Wind Turbine are considered to be one of the more efficient system of energy production nowadays, a reason that leads the main industrial companies in wind turbine construction and researchers in over the world to look for better performance and one of the ways for that is the use of the synchronous permanent magnet generator. In this context, this work is about developing an analytical model that could simulate different situation in which the synchronous generator may go through, and of course this model match perfectly with the numerical and experimental model.

Keywords: MATLAB, synchronous permanent magnet generator, wind turbine, analytical model

Procedia PDF Downloads 549

Authors: Cynthia Zgheib, Yonna Sacre

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Pregnancy, this particular moment in the life of a woman, requires monitoring of eating behavior changes. However, the food choices during pregnancy should be varied and healthy, including the consumption of different food groups. Nutritional status is the process of acquisition and consumption of food. Therefore, a varied diet is associated with good nutritional status. This is why the nutrition education is a strategy commonly applied to improve maternal nutrition during pregnancy. Thus, it is crucial to assess 'The eating behavior and nutritional status of pregnant women living in Keserwan Lebanon.' In order to evaluate the association of different persona, socioeconomic and sociodemographic factors with the eating behavior and nutrition in the concerned study category, a cross-sectional descriptive study was conducted on a sample of 150 pregnant women aging between 18 and 40 years randomly selected from the hospitals and clinics located in Keserwan area and equally distributed between different cities and villages of the area according to altitude. The purpose of this study was to evaluate the eating behavior of the concerned population and to compare it to the recommendation of the food guide pyramid, their level of food awareness and finally to analyze their blood tests in order to detect any nutrients deficiency that they may face during the course of their pregnancy. Sociodemographic, lifestyle, eating behaviour, health, eating patterns, awareness, and food frequency questionnaire (FFQ) were collected through a validated questionnaire specifically adapted for the purpose of the study. Statistical analysis was carried out, and multivariate models were used in order to evaluate the association between several independent variables and the eating behaviour and nutritional status of Lebanese pregnant women The final analysis has shown that 48.7% of pregnant women were aged between 30 and 40 years old, 56% had a normal BMI between 18.5 and 24.9, thus age affects the eating behavior, so the older are the pregnant women, and the healthier is their eating behavior. In fact, 80.7% had acceptable food behavior which is based on an equilibrium between both quantity and quality of food, although the recommended foods are foods found in the food pyramid and available in the Lebanese diet. In addition, 68% had an acceptable level of awareness concerning the health importance of good eating habits, therefore, it is positively affecting their food choices. Moreover, 50 % have an acceptable nutritional status which is confirmed by their biological tests. Future governmental or national studies and programs could be settled aiming to increase the awareness about the good eating behaviors and nutritional status of Lebanese pregnant women.

Keywords: eating behavior, nutritional status, level of awareness, pregnant woman

Procedia PDF Downloads 256

Authors: Gabriela Silva-Maceda, Silvia Romero-Contreras

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Spanish is a more transparent language than English given that it has more direct correspondences between sounds and letters. It has become important to understand how decoding and linguistic comprehension contribute to reading comprehension in the framework of the widely known Simple View Model. This study aimed to identify the level of prediction by these two components in a sample of 1st to 4th grade children attending two schools in central Mexico (one public and one private). Within each school, ten children were randomly selected in each grade level, and their parents were asked about reading habits and socioeconomic information. In total, 79 children completed three standardized tests measuring decoding (pseudo-word reading), linguistic comprehension (understanding of paragraphs) and reading comprehension using subtests from the Clinical Evaluation of Language Fundamentals-Spanish, Fourth Edition, and the Test de Lectura y Escritura en Español (LEE). The data were analyzed using hierarchical regression, with decoding as a first step and linguistic comprehension as a second step. Results showed that decoding accounted for 19.2% of the variance in reading comprehension, while linguistic comprehension accounted for an additional 10%, adding up to 29.2% of variance explained: F (2, 75)= 15.45, p <.001. Socioeconomic status derived from parental questionnaires showed a statistically significant association with the type of school attended, X2 (3, N= 79) = 14.33, p =.002. Nonetheless when analyzing the Simple View components, only decoding differences were statistically significant (t = -6.92, df = 76.81, p < .001, two-tailed); reading comprehension differences were also significant (t = -3.44, df = 76, p = .001, two-tailed). When socioeconomic status was included in the model, it predicted a 5.9% unique variance, even when already accounting for Simple View components, adding to a 35.1% total variance explained. This three-predictor model was also significant: F (3, 72)= 12.99, p <.001. In addition, socioeconomic status was significantly correlated with the amount of non-textbook books parents reported to have at home for both adults (rho = .61, p<.001) and children (rho= .47, p<.001). Results converge with a large body of literature finding socioeconomic differences in reading comprehension; in addition this study suggests that these differences were also present in decoding skills. Although linguistic comprehension differences between schools were expected, it is argued that the test used to collect this variable was not sensitive to linguistic differences, since it came from a test to diagnose clinical language disabilities. Even with this caveat, results show that the components of the Simple View Model can predict less than a third of the variance in reading comprehension in Spanish. However, the results also suggest that a fuller model of reading comprehension is obtained when considering the family’s socioeconomic status, given the potential differences shown by the socioeconomic status association with books at home, factors that are particularly important in countries where inequality gaps are relatively large.

Keywords: decoding, linguistic comprehension, reading comprehension, simple view model, socioeconomic status, Spanish

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Authors: Shishay Kidanu, Abdullah Alhaj

Abstract:

Sinkholes in the karst terrain of Greene County, Missouri, pose significant geohazards, imposing challenges on construction and infrastructure development, with potential threats to lives and property. To address these issues, understanding the influencing factors and modeling sinkhole susceptibility is crucial for effective mitigation through strategic changes in land use planning and practices. This study utilizes geographic information system (GIS) software to collect and process diverse data, including topographic, geologic, hydrogeologic, and anthropogenic information. Nine key sinkhole influencing factors, ranging from slope characteristics to proximity to geological structures, were carefully analyzed. The Frequency Ratio method establishes relationships between attribute classes of these factors and sinkhole events, deriving class weights to indicate their relative importance. Weighted integration of these factors is accomplished using the Analytic Hierarchy Process (AHP) and the Weighted Linear Combination (WLC) method in a GIS environment, resulting in a comprehensive sinkhole susceptibility index (SSI) model for the study area. Employing Jenk's natural break classifier method, the SSI values are categorized into five distinct sinkhole susceptibility zones: very low, low, moderate, high, and very high. Validation of the model, conducted through the Area Under Curve (AUC) and Sinkhole Density Index (SDI) methods, demonstrates a robust correlation with sinkhole inventory data. The prediction rate curve yields an AUC value of 74%, indicating a 74% validation accuracy. The SDI result further supports the success of the sinkhole susceptibility model. This model offers reliable predictions for the future distribution of sinkholes, providing valuable insights for planners and engineers in the formulation of development plans and land-use strategies. Its application extends to enhancing preparedness and minimizing the impact of sinkhole-related geohazards on both infrastructure and the community.

Keywords: sinkhole, GIS, analytical hierarchy process, frequency ratio, susceptibility, Missouri

Procedia PDF Downloads 74