Search results for: curriculum models
5871 Fluid Structure Interaction of Offshore Concrete Columns under Explosion Loads
Authors: Ganga K. V. Prakhya, V. Karthigeyan
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The paper describes the influences of the fluid and structure interaction in concrete structures that support large oil platforms in the North Sea. The dynamic interaction of the fluid both in 2D and 3D are demonstrated through a Computational Fluid Dynamics analysis in the event of explosion following a gas leak inside of the concrete column. The structural response characteristics of the column in water under dynamic conditions are quite complex involving axial, radial and circumferential modes. Fluid structure interaction (FSI) modelling showed that there are some frequencies of the column in water which are not found for a column in air. For example, it was demonstrated that one of the axial breathing modes can never be simulated without the use of FSI models. The occurrence of a shift in magnitude and time of pressure from explosion following gas leak along the height of the shaft not only excited the modes of vibration involving breathing (axial), bending and squashing (radial) modes but also magnified the forces in the column. FSI models revealed that dynamic effects resulted in dynamic amplification of loads. The results are summarized from a detailed study that was carried out by the first author for the Offshore Safety Division of Health & Safety Executive United Kingdom.Keywords: concrete, explosion, fluid structure interaction, offshore structures
Procedia PDF Downloads 1885870 Students’ Perceptions of the Use of Social Media in Higher Education in Saudi Arabia
Authors: Omar Alshehri, Vic Lally
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This paper examined the attitudes of using social media tools to support learning at a university in Saudi Arabia. Moreover, it investigated the students’ current usage of these tools and examined the barriers they could face during the use of social media tools in the education process. Participants in this study were 42 university students. A web-based survey was used to collect data for this study. The results indicate that all of the students were familiar with social media and had used at least one type of social media for learning. It was found out that all students had very positive attitudes towards the use of social media and welcomed using these tools as a supplementary to the curriculum. However, the results indicated that the major barriers to using these tools in learning were distraction, opposing Islamic religious teachings, privacy issues, and cyberbullying. The study recommended that this study could be replicated at other Saudi universities to investigate factors and barriers that might affect Saudi students’ attitudes toward using social media to support learning.Keywords: barriers to social media use, benefits of social media use, higher education, Saudi Arabia, social media
Procedia PDF Downloads 1675869 Social Work Education in Gujarat: Challenges and Responses
Authors: Rajeshkumar Mahendrabhai Patel, Narendrakumar D. Vasava
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It is seen that higher education in India requires a high degree of attention for the quality. The Government of India has been putting its efforts to improvise the quality of higher education through different means such as need based changes in the policy of higher education, accreditation of the institutions of higher education and many others. The Social Work education in India started way back in Tata School of Social Sciences in the year 1936. Gradually the need for social work education was felt, and different institution started imparting social work education in different regions. Due to the poor educational policy of Gujarat state (The Concept of Self-Financed Education) different Universities initiated the MSW program on a self-financed basis. The present scenario of the Social work Education in Gujarat faces ample challenges and problems which need to be addressed consciously. The present paper will try to examine and analyze the challenges and problems such as curriculum, staffing, quality of teaching, the pattern of education etc. The probable responses to this scenario are also discussed in this paper.Keywords: social work education, challenges, problems, responses, self-financed education in Gujarat
Procedia PDF Downloads 3685868 Intercultural Competency for Teachers at the Public Multicultural Alternative School for Immigrants and Multicultural Family Student’s School Maladjustment in Korea
Authors: Kiseob Chung, Hyeonmin Kang
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This study aims to explore what is intercultural competency needed for teacher through their experience at the public multicultural alternative school. The public alternative multicultural school is an accredited school for immigrants or students from multicultural families who have experienced school maladjustment at public school. This school has self-regulation in curriculum and function of bridge to public school by helping their adaptation. In particular, this study answers the following questions: What are the most difficulties for teacher at the multicultural alternative school in comparison to public school? What competencies are required for teacher at the multicultural alternative school? Which competencies in cognitive, emotional and practical area should be more required in order for teacher to communicate with student effectively (successfully) in class and other activities in school? What is the background of that we called these competencies especially as ‘intercultural’? This study focuses to clarify teacher’s competency to help immigrants of students from multicultural background to adjust to school life with the term of intercultural competency.Keywords: intercultural competency for teacher, multicultural alternative school, multicultural students, school maladjustment
Procedia PDF Downloads 4665867 An Excellent Adventure: The Stories of National Tertiary Teaching Excellence Award Winners
Authors: Claire Goode
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This paper reports on a doctoral research project using narrative inquiry to investigate the stories of twelve national Tertiary Teaching Excellence Award winners in New Zealand. Preliminary findings highlight awardees’ views on their identity, their professional practice, and on what they consider to be excellence in tertiary teaching. The research also reports on common themes in the personal qualities that awardees describe, and on what these nationally recognised educators would like to see in place around Tertiary Teacher Development. Educators, mentors, trainers, and curriculum designers can gain a deeper understanding of what teaching excellence looks like, and of how teachers perceive their own practice and their impact on others. This may enable different interventions to develop best practice from staff, and to raise standards. It is hoped too that, by reflecting on the stories of teachers who have been recognised for ‘excellence’, educators will relate to and recognise elements of their own practice, and will feel motivated and inspired to share these with their peers and the wider academic community.Keywords: academic identity, narrative inquiry, teacher development, teaching excellence
Procedia PDF Downloads 1225866 Using iPads and Tablets in Language Teaching and Learning Process
Authors: Ece Sarigul
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It is an undeniable fact that, teachers need new strategies to communicate with students of the next generation and to shape enticing educational experiences for them. Many schools have launched iPad/ Tablets initiatives in an effort to enhance student learning. Despite their rapid adoption, the extent to which iPads / Tablets increase student engagement and learning is not well understood. This presentation aims to examine the use of iPads and Tablets in primary and high schools in Turkey as well as in the world to increase academic achievement through promotion of higher order thinking skills. In addition to explaining the ideas of school teachers and students who use the specific iPads or Tablets , various applications in schools and their use will be discussed and demonstrated in this study. The specific” iPads or Tablets” applications discussed in this presentation can be incorporated into the curriculum to assist in developing transformative practices and programs to meet the needs of a diverse student population. In the conclusion section of the presentation, there will be some suggestions for teachers about the effective use of technological devices in the classroom. This study can help educators understand better how students are currently using iPads and Tablets and shape future use.Keywords: ipads, language teaching, tablets, technology
Procedia PDF Downloads 2545865 Computer-Aided Teaching of Transformers for Undergraduates
Authors: Rajesh Kumar, Roopali Dogra, Puneet Aggarwal
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In the era of technological advancement, use of computer technology has become inevitable. Hence it has become the need of the hour to integrate software methods in engineering curriculum as a part to boost pedagogy techniques. Simulations software is a great help to graduates of disciplines such as electrical engineering. Since electrical engineering deals with high voltages and heavy instruments, extra care must be taken while operating with them. The viable solution would be to have appropriate control. The appropriate control could be well designed if engineers have knowledge of kind of waveforms associated with the system. Though these waveforms can be plotted manually, but it consumes a lot of time. Hence aid of simulation helps to understand steady state of system and resulting in better performance. In this paper computer, aided teaching of transformer is carried out using MATLAB/Simulink. The test carried out on a transformer includes open circuit test and short circuit respectively. The respective parameters of transformer are then calculated using the values obtained from open circuit and short circuit test respectively using Simulink.Keywords: computer aided teaching, open circuit test, short circuit test, simulink, transformer
Procedia PDF Downloads 3745864 The State Model of Corporate Governance
Authors: Asaiel Alohaly
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A theoretical framework for corporate governance is needed to bridge the gap between the corporate governance of private companies and State-owned Enterprises (SOEs). The two dominant models, being shareholder and stakeholder, do not always address the specific requirements and challenges posed by ‘hybrid’ companies; namely, previously national bodies that have been privatised bffu t where the government retains significant control or holds a majority of shareholders. Thus, an exploratory theoretical study is needed to identify how ‘hybrid’ companies should be defined and why the state model should be acknowledged since it is the less conspicuous model in comparison with the shareholder and stakeholder models. This research focuses on ‘the state model of corporate governance to understand the complex ownership, control pattern, goals, and corporate governance of these hybrid companies. The significance of this research lies in the fact that there is a limited available publication on the state model. The outcomes of this research are as follows. It became evident that the state model exists in the ecosystem. However, corporate governance theories have not extensively covered this model. Though, there is a lot being said about it by OECD and the World Bank. In response to this gap between theories and industry practice, this research argues for the state model, which proceeds from an understanding of the institutionally embedded character of hybrid companies where the government is either a majority of the total shares or a controlling shareholder.Keywords: corporate governance, control, shareholders, state model
Procedia PDF Downloads 1435863 Generalized Extreme Value Regression with Binary Dependent Variable: An Application for Predicting Meteorological Drought Probabilities
Authors: Retius Chifurira
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Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities
Procedia PDF Downloads 2005862 Consolidated Predictive Model of the Natural History of Breast Cancer Considering Primary Tumor and Secondary Distant Metastases Growth
Authors: Ella Tyuryumina, Alexey Neznanov
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This study is an attempt to obtain reliable data on the natural history of breast cancer growth. We analyze the opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) to try to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. The research aim is to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoMPaS and corresponding software. We are interested in: 1) modelling the whole natural history of the primary tumor and the secondary distant metastases; 2) developing adequate and precise CoMPaS which reflects relations between the primary tumor and the secondary distant metastases; 3) analyzing the CoMPaS scope of application; 4) implementing the model as a software tool. The foundation of the CoMPaS is the exponential tumor growth model, which is described by determinate nonlinear and linear equations. The CoMPaS corresponds to TNM classification. It allows to calculate different growth periods of the primary tumor and the secondary distant metastases: 1) ‘non-visible period’ for the primary tumor; 2) ‘non-visible period’ for the secondary distant metastases; 3) ‘visible period’ for the secondary distant metastases. The CoMPaS is validated on clinical data of 10-years and 15-years survival depending on the tumor stage and diameter of the primary tumor. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer growth models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. The CoMPaS model and predictive software: a) fit to clinical trials data; b) detect different growth periods of the primary tumor and the secondary distant metastases; c) make forecast of the period of the secondary distant metastases appearance; d) have higher average prediction accuracy than the other tools; e) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoMPaS: the number of doublings for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases. The CoMPaS enables, for the first time, to predict ‘whole natural history’ of the primary tumor and the secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on the primary tumor sizes. Summarizing: a) CoMPaS describes correctly the primary tumor growth of IA, IIA, IIB, IIIB (T1-4N0M0) stages without metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and inception of the secondary distant metastases.Keywords: breast cancer, exponential growth model, mathematical model, metastases in lymph nodes, primary tumor, survival
Procedia PDF Downloads 3415861 Effects of Soil-Structure Interaction on Seismic Performance of Steel Structures Equipped with Viscous Fluid Dampers
Authors: Faramarz Khoshnoudian, Saeed Vosoughiyan
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The main goal of this article is to clarify the soil-structure interaction (SSI) effects on the seismic performance of steel moment resisting frame buildings which are rested on soft soil and equipped with viscous fluid dampers (VFDs). For this purpose, detailed structural models of a ten-story SMRF with VFDs excluding and including the SSI are constructed first. In order to simulate the dynamic response of the foundation, in this paper, the simple cone model is applied. Then, the nonlinear time-history analysis of the models is conducted using three kinds of earthquake excitations with different intensities. The analysis results have demonstrated that the SSI effects on the seismic performance of a structure equipped with VFDs and supported by rigid foundation on soft soil need to be considered. Also VFDs designed based on rigid foundation hypothesis fail to achieve the expected seismic objective while SSI goes into effect.Keywords: nonlinear time-history analysis, soil-structure interaction, steel moment resisting frame building, viscous fluid dampers
Procedia PDF Downloads 3355860 A Study on Puzzle-Based Game to Teach Elementary Students to Code
Authors: Jaisoon Baek, Gyuhwan Oh
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In this study, we developed a puzzle game based on coding and a web-based management system to observe the user's learning status in real time and maximize the understanding of the coding of elementary students. We have improved upon and existing coding game which cannot be connected to textual language coding or comprehends learning state. We analyzed the syntax of various coding languages for the curriculum and provided a menu to convert icon into textual coding languages. In addition, the management system includes multiple types of tutoring, real-time analysis of user play data and feedback. Following its application in regular elementary school software classes, students reported positive effects on understanding and interest in coding were shown by students. It is expected that this will contribute to quality improvement in software education by providing contents with proven educational value by breaking away from simple learning-oriented coding games.Keywords: coding education, serious game, coding, education management system
Procedia PDF Downloads 1415859 Modeling of Long Wave Generation and Propagation via Seabed Deformation
Authors: Chih-Hua Chang
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This study uses a three-dimensional (3D) fully nonlinear model to simulate the wave generation problem caused by the movement of the seabed. The numerical model is first simplified into two dimensions and then compared with the existing two-dimensional (2D) experimental data and the 2D numerical results of other shallow-water wave models. Results show that this model is different from the earlier shallow-water wave models, with the phase being closer to the experimental results of wave propagation. The results of this study are also compared with those of the 3D experimental results of other researchers. Satisfactory results can be obtained in both the waveform and the flow field. This study assesses the application of the model to simulate the wave caused by the circular (radius r0) terrain rising or falling (moving distance bm). The influence of wave-making parameters r0 and bm are discussed. This study determines that small-range (e.g., r0 = 2, normalized by the static water depth), rising, or sinking terrain will produce significant wave groups in the far field. For large-scale moving terrain (e.g., r0 = 10), uplift and deformation will potentially generate the leading solitary-like waves in the far field.Keywords: seismic wave, wave generation, far-field waves, seabed deformation
Procedia PDF Downloads 865858 A Hybrid-Evolutionary Optimizer for Modeling the Process of Obtaining Bricks
Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton
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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions
Procedia PDF Downloads 825857 Batch Kinetic, Isotherm and Thermodynamic Studies of Copper (II) Removal from Wastewater Using HDL as Adsorbent
Authors: Nadjet Taoualit, Zoubida Chemat, Djamel-Eddine Hadj-Boussaad
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This study aims the removal of copper Cu (II) contained in wastewater by adsorption on a perfect synthesized mud. It is the materials Hydroxides Double Lamellar, HDL, prepared and synthesized by co-precipitation method at constant pH, which requires a simple titration assembly, with an inexpensive and available material in the laboratory, and also allows us better control of the composition of the reaction medium, and gives well crystallized products. A characterization of the adsorbent proved essential. Thus a range of physic-chemical analysis was performed including: FTIR spectroscopy, X-ray diffraction… The adsorption of copper ions was investigated in dispersed medium (batch). A systematic study of various parameters (amount of support, contact time, initial copper concentration, temperature, pH…) was performed. Adsorption kinetic data were tested using pseudo-first order, pseudo-second order, Bangham's equation and intra-particle diffusion models. The equilibrium data were analyzed using Langmuir, Freundlich, Tempkin and other isotherm models at different doses of HDL. The thermodynamics parameters were evaluated at different temperatures. The results have established good potentiality for the HDL to be used as a sorbent for the removal of Copper from wastewater.Keywords: adsoption, copper, HDL, isotherm
Procedia PDF Downloads 2755856 An Ensemble Deep Learning Architecture for Imbalanced Classification of Thoracic Surgery Patients
Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi
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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection
Procedia PDF Downloads 1455855 Supersymmetry versus Compositeness: 2-Higgs Doublet Models Tell the Story
Authors: S. De Curtis, L. Delle Rose, S. Moretti, K. Yagyu
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Supersymmetry and compositeness are the two prevalent paradigms providing both a solution to the hierarchy problem and motivation for a light Higgs boson state. An open door towards the solution is found in the context of 2-Higgs Doublet Models (2HDMs), which are necessary to supersymmetry and natural within compositeness in order to enable Electro-Weak Symmetry Breaking. In scenarios of compositeness, the two isospin doublets arise as pseudo Nambu-Goldstone bosons from the breaking of SO(6). By calculating the Higgs potential at one-loop level through the Coleman-Weinberg mechanism from the explicit breaking of the global symmetry induced by the partial compositeness of fermions and gauge bosons, we derive the phenomenological properties of the Higgs states and highlight the main signatures of this Composite 2-Higgs Doublet Model at the Large Hadron Collider. These include modifications to the SM-like Higgs couplings as well as production and decay channels of heavier Higgs bosons. We contrast the properties of this composite scenario to the well-known ones established in supersymmetry, with the MSSM being the most notorious example. We show how 2HDM spectra of masses and couplings accessible at the Large Hadron Collider may allow one to distinguish between the two paradigms.Keywords: beyond the standard model, composite Higgs, supersymmetry, Two-Higgs Doublet Model
Procedia PDF Downloads 1265854 Association of Temperature Factors with Seropositive Results against Selected Pathogens in Dairy Cow Herds from Central and Northern Greece
Authors: Marina Sofia, Alexios Giannakopoulos, Antonia Touloudi, Dimitris C Chatzopoulos, Zoi Athanasakopoulou, Vassiliki Spyrou, Charalambos Billinis
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Fertility of dairy cattle can be affected by heat stress when the ambient temperature increases above 30°C and the relative humidity ranges from 35% to 50%. The present study was conducted on dairy cattle farms during summer months in Greece and aimed to identify the serological profile against pathogens that could affect fertility and to associate the positive serological results at herd level with temperature factors. A total of 323 serum samples were collected from clinically healthy dairy cows of 8 herds, located in Central and Northern Greece. ELISA tests were performed to detect antibodies against selected pathogens that affect fertility, namely Chlamydophila abortus, Coxiella burnetii, Neospora caninum, Toxoplasma gondii and Infectious Bovine Rhinotracheitis Virus (IBRV). Eleven climatic variables were derived from the WorldClim version 1.4. and ArcGIS V.10.1 software was used for analysis of the spatial information. Five different MaxEnt models were applied to associate the temperature variables with the locations of seropositive Chl. abortus, C. burnetii, N. caninum, T. gondii and IBRV herds (one for each pathogen). The logistic outputs were used for the interpretation of the results. ROC analyses were performed to evaluate the goodness of fit of the models’ predictions. Jackknife tests were used to identify the variables with a substantial contribution to each model. The seropositivity rates of pathogens varied among the 8 herds (0.85-4.76% for Chl. abortus, 4.76-62.71% for N. caninum, 3.8-43.47% for C. burnetii, 4.76-39.28% for T. gondii and 47.83-78.57% for IBRV). The variables of annual temperature range, mean diurnal range and maximum temperature of the warmest month gave a contribution to all five models. The regularized training gains, the training AUCs and the unregularized training gains were estimated. The mean diurnal range gave the highest gain when used in isolation and decreased the gain the most when it was omitted in the two models for seropositive Chl.abortus and IBRV herds. The annual temperature range increased the gain when used alone and decreased the gain the most when it was omitted in the models for seropositive C. burnetii, N. caninum and T. gondii herds. In conclusion, antibodies against Chl. abortus, C. burnetii, N. caninum, T. gondii and IBRV were detected in most herds suggesting circulation of pathogens that could cause infertility. The results of the spatial analyses demonstrated that the annual temperature range, mean diurnal range and maximum temperature of the warmest month could affect positively the possible pathogens’ presence. Acknowledgment: This research has been co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH–CREATE–INNOVATE (project code: T1EDK-01078).Keywords: dairy cows, seropositivity, spatial analysis, temperature factors
Procedia PDF Downloads 1995853 Development of Earthquake and Typhoon Loss Models for Japan, Specifically Designed for Underwriting and Enterprise Risk Management Cycles
Authors: Nozar Kishi, Babak Kamrani, Filmon Habte
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Natural hazards such as earthquakes and tropical storms, are very frequent and highly destructive in Japan. Japan experiences, every year on average, more than 10 tropical cyclones that come within damaging reach, and earthquakes of moment magnitude 6 or greater. We have developed stochastic catastrophe models to address the risk associated with the entire suite of damaging events in Japan, for use by insurance, reinsurance, NGOs and governmental institutions. KCC’s (Karen Clark and Company) catastrophe models are procedures constituted of four modular segments: 1) stochastic events sets that would represent the statistics of the past events, hazard attenuation functions that could model the local intensity, vulnerability functions that would address the repair need for local buildings exposed to the hazard, and financial module addressing policy conditions that could estimates the losses incurring as result of. The events module is comprised of events (faults or tracks) with different intensities with corresponding probabilities. They are based on the same statistics as observed through the historical catalog. The hazard module delivers the hazard intensity (ground motion or wind speed) at location of each building. The vulnerability module provides library of damage functions that would relate the hazard intensity to repair need as percentage of the replacement value. The financial module reports the expected loss, given the payoff policies and regulations. We have divided Japan into regions with similar typhoon climatology, and earthquake micro-zones, within each the characteristics of events are similar enough for stochastic modeling. For each region, then, a set of stochastic events is developed that results in events with intensities corresponding to annual occurrence probabilities that are of interest to financial communities; such as 0.01, 0.004, etc. The intensities, corresponding to these probabilities (called CE, Characteristics Events) are selected through a superstratified sampling approach that is based on the primary uncertainty. Region specific hazard intensity attenuation functions followed by vulnerability models leads to estimation of repair costs. Extensive economic exposure model addresses all local construction and occupancy types, such as post-linter Shinand Okabe wood, as well as concrete confined in steel, SRC (Steel-Reinforced Concrete), high-rise.Keywords: typhoon, earthquake, Japan, catastrophe modelling, stochastic modeling, stratified sampling, loss model, ERM
Procedia PDF Downloads 2695852 Effect of Storey Number on Vierendeel Action in Progressive Collapse of RC Frames
Authors: Qian Huiya, Feng Lin
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The progressive collapse of reinforced concrete (RC) structures will cause huge casualties and property losses. Therefore, it is necessary to evaluate the ability of structures against progressive collapse accurately. This paper numerically investigated the effect of storey number on the mechanism and quantitative contribution of the Vierendeel action (VA) in progressive collapse under corner column removal scenario. First, finite element (FE) models of multi-storey RC frame structures were developed using LS-DYNA. Then, the accuracy of the modeling technique was validated by test results conducted by the authors. Last, the validated FE models were applied to investigated the structural behavior of the RC frames with different storey numbers from one to six storeys. Results found the multi-storey substructure formed additional plastic hinges at the beam ends near the corner column in the second to top storeys, and at the lower end of the corner column in the first storey. The average ultimate resistance of each storey of the multi-storey substructures were increased by 14.0% to 18.5% compared with that of the single-storey substructure experiencing no VA. The contribution of VA to the ultimate resistance was decreased with the increase of the storey number.Keywords: progressive collapse, reinforced concrete structure, storey number, Vierendeel action
Procedia PDF Downloads 635851 Forecasting Thermal Energy Demand in District Heating and Cooling Systems Using Long Short-Term Memory Neural Networks
Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios
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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand
Procedia PDF Downloads 1425850 Investigation of Rehabilitation Effects on Fire Damaged High Strength Concrete Beams
Authors: Eun Mi Ryu, Ah Young An, Ji Yeon Kang, Yeong Soo Shin, Hee Sun Kim
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As the number of fire incidents has been increased, fire incidents significantly damage economy and human lives. Especially when high strength reinforced concrete is exposed to high temperature due to a fire, deterioration occurs such as loss in strength and elastic modulus, cracking, and spalling of the concrete. Therefore, it is important to understand risk of structural safety in building structures by studying structural behaviors and rehabilitation of fire damaged high strength concrete structures. This paper aims at investigating rehabilitation effect on fire damaged high strength concrete beams using experimental and analytical methods. In the experiments, flexural specimens with high strength concrete are exposed to high temperatures according to ISO 834 standard time temperature curve. After heated, the fire damaged reinforced concrete (RC) beams having different cover thicknesses and fire exposure time periods are rehabilitated by removing damaged part of cover thickness and filling polymeric mortar into the removed part. From four-point loading test, results show that maximum loads of the rehabilitated RC beams are 1.8~20.9% higher than those of the non-fire damaged RC beam. On the other hand, ductility ratios of the rehabilitated RC beams are decreased than that of the non-fire damaged RC beam. In addition, structural analyses are performed using ABAQUS 6.10-3 with same conditions as experiments to provide accurate predictions on structural and mechanical behaviors of rehabilitated RC beams. For the rehabilitated RC beam models, integrated temperature–structural analyses are performed in advance to obtain geometries of the fire damaged RC beams. After spalled and damaged parts are removed, rehabilitated part is added to the damaged model with material properties of polymeric mortar. Three dimensional continuum brick elements are used for both temperature and structural analyses. The same loading and boundary conditions as experiments are implemented to the rehabilitated beam models and nonlinear geometrical analyses are performed. Structural analytical results show good rehabilitation effects, when the result predicted from the rehabilitated models are compared to structural behaviors of the non-damaged RC beams. In this study, fire damaged high strength concrete beams are rehabilitated using polymeric mortar. From four point loading tests, it is found that such rehabilitation is able to make the structural performance of fire damaged beams similar to non-damaged RC beams. The predictions from the finite element models show good agreements with the experimental results and the modeling approaches can be used to investigate applicability of various rehabilitation methods for further study.Keywords: fire, high strength concrete, rehabilitation, reinforced concrete beam
Procedia PDF Downloads 4455849 Dynamic Wind Effects in Tall Buildings: A Comparative Study of Synthetic Wind and Brazilian Wind Standard
Authors: Byl Farney Cunha Junior
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In this work the dynamic three-dimensional analysis of a 47-story building located in Goiania city when subjected to wind loads generated using both the Wind Brazilian code, NBR6123 (ABNT, 1988) and the Synthetic-Wind method is realized. To model the frames three different methodologies are used: the shear building model and both bi and three-dimensional finite element models. To start the analysis, a plane frame is initially studied to validate the shear building model and, in order to compare the results of natural frequencies and displacements at the top of the structure the same plane frame was modeled using the finite element method through the SAP2000 V10 software. The same steps were applied to an idealized 20-story spacial frame that helps in the presentation of the stiffness correction process applied to columns. Based on these models the two methods used to generate the Wind loads are presented: a discrete model proposed in the Wind Brazilian code, NBR6123 (ABNT, 1988) and the Synthetic-Wind method. The method uses the Davenport spectrum which is divided into a variety of frequencies to generate the temporal series of loads. Finally, the 47- story building was analyzed using both the three-dimensional finite element method through the SAP2000 V10 software and the shear building model. The models were loaded with Wind load generated by the Wind code NBR6123 (ABNT, 1988) and by the Synthetic-Wind method considering different wind directions. The displacements and internal forces in columns and beams were compared and a comparative study considering a situation of a full elevated reservoir is realized. As can be observed the displacements obtained by the SAP2000 V10 model are greater when loaded with NBR6123 (ABNT, 1988) wind load related to the permanent phase of the structure’s response.Keywords: finite element method, synthetic wind, tall buildings, shear building
Procedia PDF Downloads 2735848 Integration of an Evidence-Based Medicine Curriculum into Physician Assistant Education: Teaching for Today and the Future
Authors: Martina I. Reinhold, Theresa Bacon-Baguley
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Background: Medical knowledge continuously evolves and to help health care providers to stay up-to-date, evidence-based medicine (EBM) has emerged as a model. The practice of EBM requires new skills of the health care provider, including directed literature searches, the critical evaluation of research studies, and the direct application of the findings to patient care. This paper describes the integration and evaluation of an evidence-based medicine course sequence into a Physician Assistant curriculum. This course sequence teaches students to manage and use the best clinical research evidence to competently practice medicine. A survey was developed to assess the outcomes of the EBM course sequence. Methodology: The cornerstone of the three-semester sequence of EBM are interactive small group discussions that are designed to introduce students to the most clinically applicable skills to identify, manage and use the best clinical research evidence to improve the health of their patients. During the three-semester sequence, the students are assigned each semester to participate in small group discussions that are facilitated by faculty with varying background and expertise. Prior to the start of the first EBM course in the winter semester, PA students complete a knowledge-based survey that was developed by the authors to assess the effectiveness of the course series. The survey consists of 53 Likert scale questions that address the nine objectives for the course series. At the end of the three semester course series, the same survey was given to all students in the program and the results from before, and after the sequence of EBM courses are compared. Specific attention is paid to overall performance of students in the nine course objectives. Results: We find that students from the Class of 2016 and 2017 consistently improve (as measured by percent correct responses on the survey tool) after the EBM course series (Class of 2016: Pre- 62% Post- 75%; Class of 2017: Pre- 61 % Post-70%). The biggest increase in knowledge was observed in the areas of finding and evaluating the evidence, with asking concise clinical questions (Class of 2016: Pre- 61% Post- 81%; Class of 2017: Pre- 61 % Post-75%) and searching the medical database (Class of 2016: Pre- 24% Post- 65%; Class of 2017: Pre- 35 % Post-66 %). Questions requiring students to analyze, evaluate and report on the available clinical evidence regarding diagnosis showed improvement, but to a lesser extend (Class of 2016: Pre- 56% Post- 77%; Class of 2017: Pre- 56 % Post-61%). Conclusions: Outcomes identified that students did gain skills which will allow them to apply EBM principles. In addition, the outcomes of the knowledge-based survey allowed the faculty to focus on areas needing improvement, specifically the translation of best evidence into patient care. To address this area, the clinical faculty developed case scenarios that were incorporated into the lecture and discussion sessions, allowing students to better connect the research studies with patient care. Students commented that ‘class discussion and case examples’ contributed most to their learning and that ‘it was helpful to learn how to develop research questions and how to analyze studies and their significance to a potential client’. As evident by the outcomes, the EBM courses achieved the goals of the course and were well received by the students.Keywords: evidence-based medicine, clinical education, assessment tool, physician assistant
Procedia PDF Downloads 1255847 Human Action Recognition Using Wavelets of Derived Beta Distributions
Authors: Neziha Jaouedi, Noureddine Boujnah, Mohamed Salim Bouhlel
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In the framework of human machine interaction systems enhancement, we focus throw this paper on human behavior analysis and action recognition. Human behavior is characterized by actions and reactions duality (movements, psychological modification, verbal and emotional expression). It’s worth noting that many information is hidden behind gesture, sudden motion points trajectories and speeds, many research works reconstructed an information retrieval issues. In our work we will focus on motion extraction, tracking and action recognition using wavelet network approaches. Our contribution uses an analysis of human subtraction by Gaussian Mixture Model (GMM) and body movement through trajectory models of motion constructed from kalman filter. These models allow to remove the noise using the extraction of the main motion features and constitute a stable base to identify the evolutions of human activity. Each modality is used to recognize a human action using wavelets of derived beta distributions approach. The proposed approach has been validated successfully on a subset of KTH and UCF sports database.Keywords: feautures extraction, human action classifier, wavelet neural network, beta wavelet
Procedia PDF Downloads 4115846 An Analytical Wall Function for 2-D Shock Wave/Turbulent Boundary Layer Interactions
Authors: X. Wang, T. J. Craft, H. Iacovides
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When handling the near-wall regions of turbulent flows, it is necessary to account for the viscous effects which are important over the thin near-wall layers. Low-Reynolds- number turbulence models do this by including explicit viscous and also damping terms which become active in the near-wall regions, and using very fine near-wall grids to properly resolve the steep gradients present. In order to overcome the cost associated with the low-Re turbulence models, a more advanced wall function approach has been implemented within OpenFoam and tested together with a standard log-law based wall function in the prediction of flows which involve 2-D shock wave/turbulent boundary layer interactions (SWTBLIs). On the whole, from the calculation of the impinging shock interaction, the three turbulence modelling strategies, the Lauder-Sharma k-ε model with Yap correction (LS), the high-Re k-ε model with standard wall function (SWF) and analytical wall function (AWF), display good predictions of wall-pressure. However, the SWF approach tends to underestimate the tendency of the flow to separate as a result of the SWTBLI. The analytical wall function, on the other hand, is able to reproduce the shock-induced flow separation and returns predictions similar to those of the low-Re model, using a much coarser mesh.Keywords: SWTBLIs, skin-friction, turbulence modeling, wall function
Procedia PDF Downloads 3465845 An Adaptable Semi-Numerical Anisotropic Hyperelastic Model for the Simulation of High Pressure Forming
Authors: Daniel Tscharnuter, Eliza Truszkiewicz, Gerald Pinter
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High-quality surfaces of plastic parts can be achieved in a very cost-effective manner using in-mold processes, where e.g. scratch resistant or high gloss polymer films are pre-formed and subsequently receive their support structure by injection molding. The pre-forming may be done by high-pressure forming. In this process, a polymer sheet is heated and subsequently formed into the mold by pressurized air. Due to the heat transfer to the cooled mold the polymer temperature drops below its glass transition temperature. This ensures that the deformed microstructure is retained after depressurizing, giving the sheet its final formed shape. The development of a forming process relies heavily on the experience of engineers and trial-and-error procedures. Repeated mold design and testing cycles are however both time- and cost-intensive. It is, therefore, desirable to study the process using reliable computer simulations. Through simulations, the construction of the mold and the effect of various process parameters, e.g. temperature levels, non-uniform heating or timing and magnitude of pressure, on the deformation of the polymer sheet can be analyzed. Detailed knowledge of the deformation is particularly important in the forming of polymer films with integrated electro-optical functions. Care must be taken in the placement of devices, sensors and electrical and optical paths, which are far more sensitive to deformation than the polymers. Reliable numerical prediction of the deformation of the polymer sheets requires sophisticated material models. Polymer films are often either transversely isotropic or orthotropic due to molecular orientations induced during manufacturing. The anisotropic behavior affects the resulting strain field in the deformed film. For example, parts of the same shape but different strain fields may be created by varying the orientation of the film with respect to the mold. The numerical simulation of the high-pressure forming of such films thus requires material models that can capture the nonlinear anisotropic mechanical behavior. There are numerous commercial polymer grades for the engineers to choose from when developing a new part. The effort required for comprehensive material characterization may be prohibitive, especially when several materials are candidates for a specific application. We, therefore, propose a class of models for compressible hyperelasticity, which may be determined from basic experimental data and which can capture key features of the mechanical response. Invariant-based hyperelastic models with a reduced number of invariants are formulated in a semi-numerical way, such that the models are determined from a single uniaxial tensile tests for isotropic materials, or two tensile tests in the principal directions for transversely isotropic or orthotropic materials. The simulation of the high pressure forming of an orthotropic polymer film is finally done using an orthotropic formulation of the hyperelastic model.Keywords: hyperelastic, anisotropic, polymer film, thermoforming
Procedia PDF Downloads 6175844 The Impact of a Simulated Teaching Intervention on Preservice Teachers’ Sense of Professional Identity
Authors: Jade V. Rushby, Tony Loughland, Tracy L. Durksen, Hoa Nguyen, Robert M. Klassen
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This paper reports a study investigating the development and implementation of an online multi-session ‘scenario-based learning’ (SBL) program administered to preservice teachers in Australia. The transition from initial teacher education to the teaching profession can present numerous cognitive and psychological challenges for early career teachers. Therefore, the identification of additional supports, such as scenario-based learning, that can supplement existing teacher education programs may help preservice teachers to feel more confident and prepared for the realities and complexities of teaching. Scenario-based learning is grounded in situated learning theory which holds that learning is most powerful when it is embedded within its authentic context. SBL exposes participants to complex and realistic workplace situations in a supportive environment and has been used extensively to help prepare students in other professions, such as legal and medical education. However, comparatively limited attention has been paid to investigating the effects of SBL in teacher education. In the present study, the SBL intervention provided participants with the opportunity to virtually engage with school-based scenarios, reflect on how they might respond to a series of plausible response options, and receive real-time feedback from experienced educators. The development process involved several stages, including collaboration with experienced educators to determine the scenario content based on ‘critical incidents’ they had encountered during their teaching careers, the establishment of the scoring key, the development of the expert feedback, and an extensive review process to refine the program content. The 4-part SBL program focused on areas that can be challenging in the beginning stages of a teaching career, including managing student behaviour and workload, differentiating the curriculum, and building relationships with colleagues, parents, and the community. Results from prior studies implemented by the research group using a similar 4-part format have shown a statistically significant increase in preservice teachers’ self-efficacy and classroom readiness from the pre-test to the final post-test. In the current research, professional teaching identity - incorporating self-efficacy, motivation, self-image, satisfaction, and commitment to teaching - was measured over six weeks at multiple time points: before, during, and after the 4-part scenario-based learning program. Analyses included latent growth curve modelling to assess the trajectory of change in the outcome variables throughout the intervention. The paper outlines (1) the theoretical underpinnings of SBL, (2) the development of the SBL program and methodology, and (3) the results from the study, including the impact of the SBL program on aspects of participating preservice teachers’ professional identity. The study shows how SBL interventions can be implemented alongside the initial teacher education curriculum to help prepare preservice teachers for the transition from student to teacher.Keywords: classroom simulations, e-learning, initial teacher education, preservice teachers, professional learning, professional teaching identity, scenario-based learning, teacher development
Procedia PDF Downloads 715843 International College Students Understand Entrepreneurial Readiness and Business-Related Skills: A Qualitative Study
Authors: Aleksandar Chonevski
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The free-market economy provides many opportunities for entrepreneurship or starting one’s own business, attracting many students to study business at for-profit colleges in the United States. This is also true for international students, many of whom are filled with the hope of making a better life for themselves and their families through entrepreneurial endeavors. This qualitative research showed that not all graduates business students start their own business. In investigating this phenomenon, the effectiveness of entrepreneurship curricula at international colleges needs to be examined in order to adjust, improve and reform entrepreneurship curricula. This qualitative study will explore how business skills learned in college for-profit play a role in the entrepreneurial readiness of undergraduate business students in the south Florida. Business curricula helps international students achieve goals and transform their actions to understand challenges in a corporate society. Students will be interviewed to gain information about the students’ experience with entrepreneurship curricula in a for-profit college in south Florida.Keywords: business skills, college curriculum, entrepreneurial readiness, international students
Procedia PDF Downloads 765842 Models of Bilingual Education in Majority Language Contexts: An Exploratory Study of Bilingual Programmes in Qatari Primary Schools
Authors: Fatma Al-Maadheed
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Following an ethnographic approach this study explored bilingual programmes offered by two types of primary schools in Qatar: international and Independent schools. Qatar with its unique linguistic and socio-economic situation launched a new initiative for educatiobnal development in 2001 but with hardly any research linked to theses changes. The study reveals that the Qatari bilingual schools context was one of heteroglossia, with three codes in operation: Modern Standard Arabic, Colloquial Arabic dialects and English. The two schools adopted different models of bilingualism. The international school adopted a strict separation policy between the two languages following a monoglossic belief. The independent school was found to apply a flexible language policy. The study also highlighted the daily challnges produced from the diglossia situation in Qatar, the difference between students and teacher dialect as well as acquiring literacy in the formal language. In addition to an abscence of a clear language policy in Schools, the study brought attention to the instructional methods utilised in language teaching which are mostly associated with successful bilingual education.Keywords: diglossia, instructional methods, language policy, qatari primary schools
Procedia PDF Downloads 473