Search results for: root uptake models

Authors: Pierre-Marie Basset, Gabriel Reboul, Binh DangVu, Sébastien Mercier

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Rotorcraft provides invaluable services thanks to their Vertical Take-Off and Landing (VTOL), hover and low speed capabilities. Yet their use is still often limited by their cost and environmental impact, especially noise and energy consumption. One of the main brakes to the expansion of the use of rotorcraft for urban missions is the environmental impact. The first main concern for the population is the noise. In order to develop the transversal competency to assess the rotorcraft environmental footprint, a collaboration has been launched between six research departments within ONERA. The progress in terms of models and methods are capitalized into the numerical workshop C.R.E.A.T.I.O.N. “Concepts of Rotorcraft Enhanced Assessment Through Integrated Optimization Network”. A typical mission for which the environmental impact issue is of great relevance has been defined. The first milestone is to perform the pre-sizing of a reference helicopter for this mission. In a second milestone, an alternate rotorcraft concept has been defined: a tandem rotorcraft with optional propulsion. The key design trends are given for the pre-sizing of this rotorcraft aiming at a significant reduction of the global environmental impact while still giving equivalent flight performance and safety with respect to the reference helicopter. The models and methods have been improved for catching sooner and more globally, the relative variations on the environmental impact when changing the rotorcraft architecture, the pre-design variables and the operation parameters.

Keywords: environmental impact, flight performance, helicopter, multi objectives multidisciplinary optimization, rotorcraft

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Authors: Abhijeet Ostawal, Parmjit Lall

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The run times for a large strategic model that we were managing had become too long leading to delays in project delivery, increased costs and loss in productivity. Software developers are continuously working towards developing more efficient tools by changing their algorithms and processes. The issue faced by our team was how do you apply the latest technologies on validated existing models which are based on much older versions of software that do not have the latest software capabilities. The multi-model transport model that we had could only be run in sequential assignment order. Recent upgrades to the software now allowed the assignment to be run in parallel, a concept called parallelization. Parallelization is a Python script working only within the latest version of the software. A full model transfer to the latest version was not possible due to time, budget and the potential changes in trip assignment. This article is to show the method to adapt and update the Python script in such a way that it can be used in older software versions by calling the latest version and then recalling the old version for assignment model without affecting the results. Through a process of trial-and-error run time savings of up to 30-40% have been achieved. Assignment results were maintained within the older version and through this learning process we’ve applied this methodology to other even older versions of the software resulting in huge time savings, more productivity and efficiency for both client and consultant.

Keywords: model run time, demand model, parallelisation, python scripting

Procedia PDF Downloads 118

Authors: C. P. Providakis, G. M. Angeli, M. J. Favvata, N. A. Papadopoulos, C. E. Chalioris, C. G. Karayannis

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An effort for the detection of damages in the reinforcement bars of reinforced concrete members using PZTs is presented. The damage can be the result of excessive elongation of the steel bar due to steel yielding or due to local steel corrosion. In both cases the damage is simulated by considering reduced diameter of the rebar along the damaged part of its length. An integration approach based on both electro-mechanical admittance methodology and guided wave propagation technique is used to evaluate the artificial damage on the examined longitudinal steel bar. Two actuator PZTs and a sensor PZT are considered to be bonded on the examined steel bar. The admittance of the Sensor PZT is calculated using COMSOL 3.4a. Fast Furrier Transformation for a better evaluation of the results is employed. An effort for the quantification of the damage detection using the root mean square deviation (RMSD) between the healthy condition and damage state of the sensor PZT is attempted. The numerical value of the RSMD yields a level for the difference between the healthy and the damaged admittance computation indicating this way the presence of damage in the structure. Experimental measurements are also presented.

Keywords: concrete reinforcement, damage detection, electromechanical admittance, experimental measurements, finite element method, guided waves, PZT

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In robotics literature, the simultaneous localization and mapping (SLAM) is commonly associated with a priori-posteriori problem. The autonomous vehicle needs a neutral map to spontaneously track its local position, i.e., “localization” while at the same time a precise path estimation of the environment state is required for effective route planning and obstacle avoidance. On the other hand, the environmental noise factors can significantly intensify the inherent uncertainties in using odometry information and measurements obtained from the robot’s exteroceptive sensor which in return directly affect the overall performance of the corresponding SLAM. Therefore, the current work is primarily dedicated to provide a diagnostic analysis of six SLAM algorithms including FastSLAM, L-SLAM, GraphSLAM, Grid SLAM and DP-SLAM. A SLAM simulated environment consisting of two sets of landmark locations and robot waypoints was set based on modified EKF and UKF in MATLAB using two separate maps for indoor and outdoor route planning subject to natural and artificial obstacles. The simulation results are expected to provide an unbiased platform to compare the estimation performances of the five SLAM models as well as on the reliability of each SLAM model for indoor and outdoor applications.

Keywords: route planning, obstacle, estimation performance, FastSLAM, L-SLAM, GraphSLAM, Grid SLAM, DP-SLAM

Procedia PDF Downloads 444

Authors: Zh. Saffari, A. Naeimi, M. S. Ekrami-Kakhki, Kh. Khandan-Barani

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The textile industries are becoming a major source of environmental contamination because an alarming amount of dye pollutants are generated during the dyeing processes. Organic dyes are one of the largest pollutants released into wastewater from textile and other industrial processes, which have shown severe impacts on human physiology. Nano-structure compounds have gained importance in this category due their anticipated high surface area and improved reactive sites. In recent years several novel adsorbents have been reported to possess great adsorption potential due to their enhanced adsorptive capacity. Nano-MnO2 has great potential applications in environment protection field and has gained importance in this category because it has a wide variety of structure with large surface area. The diverse structures, chemical properties of manganese oxides are taken advantage of in potential applications such as adsorbents, sensor catalysis and it is also used for wide catalytic applications, such as degradation of dyes. In this study, adsorption of Methyl Violet (MV) dye from aqueous solutions onto MnO2 nanoparticles (MNP) has been investigated. The surface characterization of these nano particles was examined by Particle size analysis, Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR) spectroscopy and X-Ray Diffraction (XRD). The effects of process parameters such as initial concentration, pH, temperature and contact duration on the adsorption capacities have been evaluated, in which pH has been found to be most effective parameter among all. The data were analyzed using the Langmuir and Freundlich for explaining the equilibrium characteristics of adsorption. And kinetic models like pseudo first- order, second-order model and Elovich equation were utilized to describe the kinetic data. The experimental data were well fitted with Langmuir adsorption isotherm model and pseudo second order kinetic model. The thermodynamic parameters, such as Free energy of adsorption (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°) were also determined and evaluated.

Keywords: MnO2 nanoparticles, adsorption, methyl violet, isotherm models, kinetic models, surface chemistry

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Authors: Bunakiye R. Japheth, Ogude U. Cyril

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Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.

Keywords: control process, metrics of engineering, structured abstraction, semantic model

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Authors: Hui Zhang, Sherif Beskhyroun

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Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. This includes abnormal changes caused by the strain field and abnormal symptoms of the structure, such as damage and deterioration. Currently, deploying sensors on a large scale in a building structure is a challenge. In this study, a highly stretchable strain sensors are used in this study to collect data sets of strain generated on the surface of full-size reinforced concrete (RC) frames under extreme cyclic load application. This sensing sheet can be switched freely between the test bending strain and the axial strain to achieve two different configurations. On this basis, the deep neural network prediction model of the frame beam and frame column is established. The training results show that the method can accurately predict the strain value and has good generalization ability. The two deep neural network prediction models will also be deployed in the SHM system in the future as part of the intelligent strain sensor system.

Keywords: strain sensing sheets, deep neural networks, strain measurement, SHM system, RC frames

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Authors: Yelena Agranovich, Larissa Ageyeva, Aigul Syzdykbayeva, Violetta Tyan

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The modernization of the education system in the Republic of Kazakhstan is aimed at improving the quality of teacher training and enhancing key competencies among teachers. The current professional standard ‘Teacher’ defines the general characteristics of teachers’ activities, key competencies, and criteria according to relevant qualification categories structured on the principle of progression, thereby enabling Continuous Professional Development (CPD). The essence of CPD lies in the constant integration of new knowledge and skills that help teachers adapt to changes in the education system, in technologies, and teaching methods. This developmental process enables teachers to stay updated on recent scientific achievements, innovations, and modern pedagogical practices. Continuous learning helps teachers remain flexible and open to new developments, creating conditions for improving educational quality and fostering students' personal growth. This study aims to address the following objectives: analysis of international CPD practices, identification of conceptual foundations, and investigation of CPD implementation mechanisms in Kazakhstan. The core principles of CPD are identified as longitudinality, systematicity, and fragmentation. CPD implementation is based on various theoretical approaches: axiological, systemic, competency-based, activity-based, and learner-centered. The study analyzes leading models of teacher CPD, with a target sample that includes countries such as Australia, Japan, South Korea, England, Singapore, Sweden, Finland, and Kazakhstan. The research methods include analysis (comparative, historical, content analysis, systematic), case studies of CPD models, and synthesis and systematization of scientific data. As research results, the mechanisms for CPD implementation in Kazakhstan will be identified, along with further perspectives on transforming resources within the teacher professional development system. In comparing CPD models from various countries, it is noted that teacher CPD in the Republic of Kazakhstan: (1) is implemented through educational programs, professional development courses, teacher certification, professional networks, in-school professional development, self-education, and self-assessment; (2) includes the development of pedagogical values and competencies (tolerance, inclusivity, communication, critical thinking, creativity, reflection, etc.); (3) is carried out based on traditional forms (professional development courses, retraining) and informal forms (self-learning, self-development, experience sharing and exchange). Further research will focus on creating a digital ecosystem for teacher CPD, based on an educational platform that facilitates individualized professional development pathways for teachers (competency diagnostics, course selection, and a methodological system of course and post-course support for teachers).

Keywords: continuous professional development, CPD models, professional development, professional upgrading, teacher, teacher training

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity

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Authors: Bruce G. Wilson

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The collection of municipal solid waste at the curbside is a complex operation that is repeated daily under varying circumstances around the world. There have been several attempts to develop Monte Carlo simulation models of the waste collection process dating back almost 50 years. Despite this long history, the use of simulation modeling as a planning or optimization tool for waste collection is still extremely limited in practice. Historically, simulation modeling of waste collection systems has been hampered by the limitations of computer hardware and software and by the availability of representative input data. This paper outlines the development of a Monte Carlo simulation model that overcomes many of the limitations contained in previous models. The model uses a general purpose simulation software program that is easily capable of modeling an entire waste collection network. The model treats the stops on a waste collection route as a queue of work to be processed by a collection vehicle (or server). Input data can be collected from a variety of sources including municipal geographic information systems, global positioning system recorders on collection vehicles, and weigh scales at transfer stations or treatment facilities. The result is a flexible model that is sufficiently robust that it can model the collection activities in a large municipality, while providing the flexibility to adapt to changing conditions on the collection route.

Keywords: modeling, queues, residential waste collection, Monte Carlo simulation

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Authors: Amirhosein Moonesi Shabestary, Eckhard Krepper, Dirk Lucas

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The current PhD project comprises CFD-modeling and simulation of condensation and heat transfer inside horizontal pipes. Condensation plays an important role in emergency cooling systems of reactors. The emergency cooling system consists of inclined horizontal pipes which are immersed in a tank of subcooled water. In the case of an accident the water level in the core is decreasing, steam comes in the emergency pipes, and due to the subcooled water around the pipe, this steam will start to condense. These horizontal pipes act as a strong heat sink which is responsible for a quick depressurization of the reactor core when any accident happens. This project is defined in order to model all these processes which happening in the emergency cooling systems. The most focus of the project is on detection of different morphologies such as annular flow, stratified flow, slug flow and plug flow. This project is an ongoing project which has been started 1 year ago in Helmholtz Zentrum Dresden Rossendorf (HZDR), Fluid Dynamics department. In HZDR most in cooperation with ANSYS different models are developed for modeling multiphase flows. Inhomogeneous MUSIG model considers the bubble size distribution and is used for modeling small-scaled dispersed gas phase. AIAD (Algebraic Interfacial Area Density Model) is developed for detection of the local morphology and corresponding switch between them. The recent model is GENTOP combines both concepts. GENTOP is able to simulate co-existing large-scaled (continuous) and small-scaled (polydispersed) structures. All these models are validated for adiabatic cases without any phase change. Therefore, the start point of the current PhD project is using the available models and trying to integrate phase transition and wall condensing models into them. In order to simplify the idea of condensation inside horizontal tubes, 3 steps have been defined. The first step is the investigation of condensation inside a horizontal tube by considering only direct contact condensation (DCC) and neglect wall condensation. Therefore, the inlet of the pipe is considered to be annular flow. In this step, AIAD model is used in order to detect the interface. The second step is the extension of the model to consider wall condensation as well which is closer to the reality. In this step, the inlet is pure steam, and due to the wall condensation, a liquid film occurs near the wall which leads to annular flow. The last step will be modeling of different morphologies which are occurring inside the tube during the condensation via using GENTOP model. By using GENTOP, the dispersed phase is able to be considered and simulated. Finally, the results of the simulations will be validated by experimental data which will be available also in HZDR.

Keywords: wall condensation, direct contact condensation, AIAD model, morphology detection

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Authors: Mohammad Jamal

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Non-alcoholic fatty liver disease (NAFLD) has become one of the most chronic liver diseases, prevalent among people with morbid obesity. NAFLD does not develop clinically significant liver disease, however cirrhosis and liver cancer develop in subset and currently there are no approved therapies for the treatment of NAFLD. The study is aimed to understand the various key genes involved in the mechanism of NAFLD which can be valuable for developing diagnostic and predictive biomarkers based on their histologic stage of liver. The study was conducted on 16 male Sprague Dawley rats. The animals were divided in two groups: control group (n=8) fed on ad libitum normal chow and regular water and the cafeteria group (CAF)) (n=8) fed on high fatty/ carbohydrate diet. The animals received their respective diet from 4 weeks onwards from D.O.B until 25 weeks. Liver was extracted and RT² Profiler PCR Array was used to assess the NAFLD related genes. Histological evaluation was performed using H&E stain in liver tissue sections. Our PCR array results showed that genes involved in anti-inflammatory activity (Ifng, IL10), fatty acid uptake/oxidation (Fabp5), apoptosis (Fas), lipogenesis (Gck and Srebf1), Insulin signalling (Igfbp1) and metabolic pathway (pdk4) were upregulated in the liver of cafeteria fed obese rats. Bloated hepatocytes, displaced nucleus and higher lipid content were seen in the liver of cafeteria fed obese rats. Although Liver biopsies remain the gold standard in evaluating NAFLD, however an approach towards non-invasive markers could be used in understanding the physiology, therapeutic potential, and the targets to combat NAFLD.

Keywords: biomarkers, cafeteria diet, obesity, NAFLD

Procedia PDF Downloads 143

Authors: N. H. Adenan, M. S. M. Noorani

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River flow prediction is an essential to ensure proper management of water resources can be optimally distribute water to consumers. This study presents an analysis and prediction by using nonlinear prediction method involving monthly river flow data in Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The phase space reconstruction involves the reconstruction of one-dimensional (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. Revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) have been employed to compare prediction performance for nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show the prediction results using nonlinear prediction method is better than ARIMA and SVM. Therefore, the result of this study could be used to developed an efficient water management system to optimize the allocation water resources.

Keywords: river flow, nonlinear prediction method, phase space, local linear approximation

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Authors: Christian Louis Kühner, Florian Pfeffel, Valentin Nickolai

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Taking care of children, dependents, or pets can be a difficult and time-consuming task. Especially for part- and full-time employees, it can feel exhausting and overwhelming to meet these obligations besides working a job. Thus, working mostly at home and not having to drive to the company can save valuable time and stress. This study aims to show the influence that the working model has on the job satisfaction of employees with care responsibilities in comparison to employees who do not have such obligations. Using structural equation modeling (SEM), the three work models, “work from home”, “working remotely”, and a hybrid model, have been analyzed based on 13 influencing constructs on job satisfaction. These 13 factors have been further summarized into three groups “classic influencing factors”, “influencing factors changed by remote working”, and “new remote working influencing factors”. Based on the influencing factors on job satisfaction, an online survey was conducted with n = 684 employees from the service sector. Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. In addition, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). The SEM-analysis has shown that the most significant influencing factor on job satisfaction is “identification with the work” with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis shows that the identification with the work is the most significant factor in all three work models and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that among the employees with care responsibilities, the higher the proportion of working from home in comparison to working from the office, the more satisfied the employees are with their job. Since the work models that meet the requirements of comprehensive care led to higher job satisfaction amongst employees with such obligations, adapting as a company to such private obligations by employees can be crucial to sustained success. Conversely, the satisfaction level of the working model where employees work at the office is higher for workers without caregiving responsibilities.

Keywords: care responsibilities, home office, job satisfaction, structural equation modeling

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Authors: Hassan Athari, Abdurrahim Bolukbasi, Dogan Ciloglu

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This study represented the respiratory alveoli system, and determined the trajectory of inhaled particles more accurately using the modified three-dimensional model with deformable walls of alveoli. The study also considered the tissue tension in the model to demonstrate the effect of lung. Tissue tensions are transferred by the lung parenchyma and produce the pressure gradient. This load expands the alveoli and establishes a sub-ambient (vacuum) pressure within the lungs. Thus, at the alveolar level, the flow field and movement of alveoli wall lead to an integrated effect. In this research, we assume that the three-dimensional alveolus has a visco-elastic tissue (walls). For accurate investigation of pulmonary tissue mechanical properties on particle transport and alveolar flow field, the actual relevance between tissue movement and airflow is solved by two-way FSI (Fluid Structure Interaction) simulation technique in the alveolus. Therefore, the essence of real simulation of pulmonary breathing mechanics can be achieved by developing a coupled FSI computational model. We, therefore conduct a series of FSI simulations over a range of tissue models and breathing rates. As a result, the fluid flows and streamlines have changed during present flexible model against the rigid models and also the two-way coupling particle trajectories have changed against the one-way particle coupling.

Keywords: FSI, two-way particle coupling, alveoli, CDF

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Authors: Kaori Mori Want

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American society is a racially diverse society and there are children books that tell the importance of respecting racial differences. Through reading books, children understand the world around them little by little along with their direct interaction with the world in reality. They find role models in books, strive to be like role models, and grow confidence in who they are. Books thus nurture the mind of children. On the other hand, because of their small presence, children books for multiracial Asian American children are scarce. Multiracial Asian American population is increasing but they are still minority in number. The lack of children’s books for these children may deprive the opportunities of them to embrace their multiraciality positively because they cannot find someone like them in any books. Children books for multiracial Asian American are still not that many, but a few have been being published recently. This paper introduces children books for multiracial Asian American children, and examines how they address issues pertaining to these children, and how they could nurture their self-esteem. Many states of the US used to ban interracial marriages and interracial families and their children once were discriminated against in American society. There was even a theory called the hybrid degeneracy theory which claimed that mixed race children were inferior mentally and physically. In this negative social environment, some multiracial Asian American people report that they had trouble embracing their multiracial identity positively. Yet, children books for these children are full of positive messages. This paper will argue the importance of children books for the mental growth of multiracial Asian American children, and how these books can contribute to the development of multiculturalism in the US in general.

Keywords: critical mixed race studies in the US, hapa children literature, interracial marriage, multiraciality

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Authors: Beddiaf Abdelaziz

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The optical characteristics of thin films of silicon oxynitride SiOₓNy prepared by the Low-Pressure Chemical Vapor Deposition (LPCVD) technique have been studied. The films are elaborated from the SiH₂Cl₂, N₂O and NH₃ gaseous mixtures. The flows of SiH₂Cl₂ and (N₂O+NH₃) are 200 sccm and 160 sccm respectively. The deposited films have been characterized by ellipsometry, to model our silicon oxynitride SiOₓNy films. We have suggested two theoretical models (Maxwell Garnett and Bruggeman effective medium approximation (BEMA)). These models have been applied on silicon oxynitride considering the material as a heterogeneous medium formed by silicon oxide and silicon nitride. The model's validation was justified by the confrontation of theoretical spectra and those measured by ellipsometry. This result permits us to obtain the optical refractive coefficient of these films and their thickness. Ellipsometry analysis of the optical properties of the SiOₓNy films shows that the SiO₂ fraction decreases when the gaseous ratio NH₃/N₂O increases. Whereas the increase of this ratio leads to an increase of the silicon nitride Si3N4 fraction. The study also shows that the increasing gaseous ratio leads to a strong incorporation of nitrogen atoms in films. Also, the increasing of the SiOₓNy refractive coefficient until the SiO₂ value shows that this insulating material has good dielectric quality.

Keywords: ellipsometry, silicon oxynitrde, model, refractive coefficient, effective medium

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Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

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Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: electromyographic feature extraction, muscle status, pedaling exercise, relaxation segment

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Authors: Mokhtar Kouki Inès Rekik

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This paper focuses on the assessment of the air pollution and morbidity relationship in Tunisia. Air pollution is measured by ozone air concentration and the morbidity is measured by the number of respiratory-related restricted activity days during the 2-week period prior to the interview. Socioeconomic data are also collected in order to adjust for any confounding covariates. Our sample is composed by 407 Tunisian respondents; 44.7% are women, the average age is 35.2, near 69% are living in a house built after the 1980, and 27.8% have reported at least one day of respiratory-related restricted activity. The model consists on the regression of the number of respiratory-related restricted activity days on the air quality measure and the socioeconomic covariates. In order to correct for zero-inflation and heterogeneity, we estimate several models (Poisson, Negative binomial, Zero inflated Poisson, Poisson hurdle, Negative binomial hurdle and finite mixture Poisson models). Bootstrapping and post-stratification techniques are used in order to correct for any sample bias. According to the Akaike information criteria, the hurdle negative binomial model has the greatest goodness of fit. The main result indicates that, after adjusting for socioeconomic data, the ozone concentration increases the probability of positive number of restricted activity days.

Keywords: bootstrapping, hurdle negbin model, overdispersion, ozone concentration, respiratory-related restricted activity days

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Authors: Ghazi Faisal Najmuldeen, Wahida Amat-Fadzil, Zulkafli Hassan, Jinan B. Al-Dabbagh

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The objective of this study was to evaluate the optimum fabrication process variables to produce particleboards from oil palm fronds (OPF) particles and empty fruit bunch fiber (EFB). Response surface methodology was employed to analyse the effect of hot press temperature (150–190°C); press time (3–7 minutes) and EFB blending ratio (0–40%) on particleboards modulus of rupture, modulus of elasticity, internal bonding, water absorption and thickness swelling. A Box-Behnken experimental design was carried out to develop statistical models used for the optimisation of the fabrication process variables. All factors were found to be statistically significant on particleboards properties. The statistical analysis indicated that all models showed significant fit with experimental results. The optimum particleboards properties were obtained at optimal fabrication process condition; press temperature; 186°C, press time; 5.7 min and EFB / OPF ratio; 30.4%. Incorporating of oil palm frond and empty fruit bunch to produce particleboards has improved the particleboards properties. The OPF–EFB particleboards fabricated at optimized conditions have satisfied the ANSI A208.1–1999 specification for general purpose particleboards.

Keywords: empty fruit bunch fiber, oil palm fronds, particleboards, response surface methodology

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Authors: Zerroug Abdelhamid, Danielle Chassoux

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Various models are given to simulate homogeneous or heterogeneous cancerous tumors and extract in each case the boundary. The fractal dimension is then estimated by least squares method and compared to some previous methods.

Keywords: simulation, cancerous tumor, Markov fields, fractal dimension, extraction, recovering

Procedia PDF Downloads 365

Authors: Subzar Ahmad Bhat, Saraswati Setia, V. K.Sehgal

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During the past earthquakes, open ground storey buildings have performed poorly due to the soft storey defect. Indian Standard IS 1893:2002 allows analysis of open ground storey buildings without considering infill stiffness but with a multiplication factor 2.5 in compensation for the stiffness discontinuity. Therefore, the aim of this paper is to check the applicability of the multiplication factor of 2.5 and study behaviour of the structure after the application of the multiplication factor. For this purpose, study is performed on models considering infill stiffness using SAP 2000 (Version 14) by linear static analysis and response spectrum analysis. Total seven models are analysed and designed for the range of multiplication factor ranging from 1.25 to 2.5. The value of multiplication factor equal to 2.5 has been found on the higher side, resulting in increased dimension and percentage of reinforcement without significant enhancement beyond a certain multiplication factor. When the building with OGS is designed for values of MF higher than 1.25 considering infill stiffness soft storey effect shifts from ground storey to first storey. For the analysis of the OGS structure best way to analysis the structure is to analyse it as the frame with stiffness and strength of the infill taken into account. The provision of infill walls in the upper storeys enhances the performance of the structure in terms of displacement and storey drift controls.

Keywords: open ground storey, multiplication factor, IS 1893:2002 provisions, static analysis, response spectrum analysis, infill stiffness, equivalent strut

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Authors: Ghazi R. Reda Mahmoud Reda

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Among the metal that forms hydride´s, Mg and Ti are known as the most lightweight materials; however, they are covered with a passive layer of oxides and hydroxides and require activation treatment under high temperature ( > 300 C ) and hydrogen pressure ( > 3 MPa) before being used for storage and transport applications. It is well known that small graphite addition to Ti or Mg, lead to a dramatic change in the kinetics of mechanically induced hydrogen sorption ( uptake) and significantly stimulate the Ti-Hydrogen interaction. Many explanations were given by different authors to explain the effect of graphite addition on the performance of Ti as material for hydrogen storage. Not only graphite but also the addition of a polycyclic aromatic compound will also improve the hydrogen absorption kinetics. It will be shown that the function of carbon addition is two-fold. First carbon acts as a vacuum cleaner, which scavenges out all the interstitial oxygen that can poison or slow down hydrogen absorption. It is also important to note that oxygen favors the chemisorption of hydrogen, which is not desirable for hydrogen storage. Second, during scavenging of the interstitial oxygen, the carbon reacts with oxygen in the nano and microchannel through a highly exothermic reaction to produce carbon dioxide and monoxide which provide the necessary heat for activation and thus in the presence of carbon lower heat of activation for hydrogen absorption which is observed experimentally. Furthermore, the product of the reaction of hydrogen with the carbon oxide will produce water which due to ball milling hydrolyze to produce the linear H5O2 + this will reconstruct the primary structure of the nanocarbon to form secondary structure, where the primary structure (a sheet of carbon) are connected through hydrogen bonding. It is the space between these sheets where physisorption or defect mediated sorption occurs.

Keywords: metal forming hydrides, polar molecule impurities, titanium, phase diagram, hydrogen absorption

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Authors: Jaan-Willem Simon, Bertram Stier, Brett Bednarcyk, Evan Pineda, Stefanie Reese

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Textile composites, in which the reinforcing fibers are woven or braided, have become very popular in numerous applications in aerospace, automotive, and maritime industry. These textile composites are advantageous due to their ease of manufacture, damage tolerance, and relatively low cost. However, physics-based modeling of the mechanical behavior of textile composites is challenging. Compared to their unidirectional counterparts, textile composites introduce additional geometric complexities, which cause significant local stress and strain concentrations. Since these internal concentrations are primary drivers of nonlinearity, damage, and failure within textile composites, they must be taken into account in order for the models to be predictive. The macro-scale approach to modeling textile-reinforced composites treats the whole composite as an effective, homogenized material. This approach is very computationally efficient, but it cannot be considered predictive beyond the elastic regime because the complex microstructural geometry is not considered. Further, this approach can, at best, offer a phenomenological treatment of nonlinear deformation and failure. In contrast, the mesoscale approach to modeling textile composites explicitly considers the internal geometry of the reinforcing tows, and thus, their interaction, and the effects of their curved paths can be modeled. The tows are treated as effective (homogenized) materials, requiring the use of anisotropic material models to capture their behavior. Finally, the micro-scale approach goes one level lower, modeling the individual filaments that constitute the tows. This paper will compare meso- and micro-scale approaches to modeling the deformation, damage, and failure of textile-reinforced polymer matrix composites. For the mesoscale approach, the woven composite architecture will be modeled using the finite element method, and an anisotropic damage model for the tows will be employed to capture the local nonlinear behavior. For the micro-scale, two different models will be used, the one being based on the finite element method, whereas the other one makes use of an embedded semi-analytical approach. The goal will be the comparison and evaluation of these approaches to modeling textile-reinforced composites in terms of accuracy, efficiency, and utility.

Keywords: multiscale modeling, continuum damage model, damage interaction, textile composites

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Authors: John Paul Q. Tomas, Mark Wilson L. de los Reyes, Kirsten Joyce P. Vasquez

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The most frequent type of fracture is a wrist fracture, which often makes it difficult for medical professionals to find and locate. In this study, fractures in wrist x-ray pictures were located and identified using deep learning and computer vision. The researchers used image filtering, masking, morphological operations, and data augmentation for the image preprocessing and trained the RetinaNet and Faster R-CNN models with ResNet50 backbones and Adam optimizers separately for each image filtering technique and projection. The RetinaNet model with Anisotropic Diffusion Smoothing filter trained with 50 epochs has obtained the greatest accuracy of 99.14%, precision of 100%, sensitivity/recall of 98.41%, specificity of 100%, and an IoU score of 56.44% for the Posteroanterior projection utilizing augmented data. For the Lateral projection using augmented data, the RetinaNet model with an Anisotropic Diffusion filter trained with 50 epochs has produced the highest accuracy of 98.40%, precision of 98.36%, sensitivity/recall of 98.36%, specificity of 98.43%, and an IoU score of 58.69%. When comparing the test results of the different individual projections, models, and image filtering techniques, the Anisotropic Diffusion filter trained with 50 epochs has produced the best classification and regression scores for both projections.

Keywords: Artificial Intelligence, Computer Vision, Wrist Fracture, Deep Learning

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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Authors: Mahdi Shaghaghi, Amir Ghaebi, Fariba Ahmadi

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Purpose: The main purpose of the present research is to analyze the knowledge creation environment at a Iranian University (Alzahra University) as a typical University in Iran, using a combination of the i-System and Ba models. This study is necessary for understanding the determinants of knowledge creation at Alzahra University as a typical University in Iran. Methodology: To carry out the present research, which is an applied study in terms of purpose, a descriptive survey method was used. In this study, a combination of the i-System and Ba models has been used to analyze the knowledge creation environment at Alzahra University. i-System consists of 5 constructs including intervention (input), intelligence (process), involvement (process), imagination (process), and integration (output). The Ba environment has three pillars, namely the infrastructure, the agent, and the information. The integration of these two models resulted in 11 constructs which were as follows: intervention (input), infrastructure-intelligence, agent-intelligence, information-intelligence (process); infrastructure-involvement, agent-involvement, information-involvement (process); infrastructure-imagination, agent-imagination, information-imagination (process); and integration (output). These 11 constructs were incorporated into a 52-statement questionnaire and the validity and reliability of the questionnaire were examined and confirmed. The statistical population included the faculty members of Alzahra University (344 people). A total of 181 participants were selected through the stratified random sampling technique. The descriptive statistics, binomial test, regression analysis, and structural equation modeling (SEM) methods were also utilized to analyze the data. Findings: The research findings indicated that among the 11 research constructs, the levels of intervention, information-intelligence, infrastructure-involvement, and agent-imagination constructs were average and not acceptable. The levels of infrastructure-intelligence and information-imagination constructs ranged from average to low. The levels of agent-intelligence and information-involvement constructs were also completely average. The level of infrastructure-imagination construct was average to high and thus was considered acceptable. The levels of agent-involvement and integration constructs were above average and were in a highly acceptable condition. Furthermore, the regression analysis results indicated that only two constructs, viz. the information-imagination and agent-involvement constructs, positively and significantly correlate with the integration construct. The results of the structural equation modeling also revealed that the intervention, intelligence, and involvement constructs are related to the integration construct with the complete mediation of imagination. Discussion and conclusion: The present research suggests that knowledge creation at Alzahra University relatively complies with the combination of the i-System and Ba models. Unlike this model, the intervention, intelligence, and involvement constructs are not directly related to the integration construct and this seems to have three implications: 1) the information sources are not frequently used to assess and identify the research biases; 2) problem finding is probably of less concern at the end of studies and at the time of assessment and validation; 3) the involvement of others has a smaller role in the summarization, assessment, and validation of the research.

Keywords: i-System, Ba model , knowledge creation , knowledge management, knowledge creation environment, Iranian Universities

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Authors: Vartan Ahrens Kayayan, Mattias Gustafsson, Erik Dotzauer

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The European Union is introducing the positive energy district concept, which has the goal to reduce overall carbon dioxide emissions. Other studies have already mapped the make-up of such districts, and reviewed their definitions and where they are positioned. The Swedish energy system is unique compared to others in Europe, due to the implementation of low-carbon electricity and heat energy sources and high uptake of district heating. The goal for this paper is to start the discussion about how the concept of positive energy districts can best be applied to the Swedish context and meet their mitigation goals. To explore how these differences impact the formation of positive energy districts, two cases were analyzed for their methods and how these integrate into the Swedish energy system: a district in Uppsala with a focus on energy and another in Helsingborg with a focus on climate. The case in Uppsala uses primary energy calculations which can be critisied but take a virtual border that allows for its surrounding system to be considered. The district in Helsingborg has a complex methodology for considering the life cycle emissions of the neighborhood. It is successful in considering the energy balance on a monthly basis, but it can be problematized in terms of creating sub-optimized systems due to setting tight geographical constraints. The discussion of shaping the definitions and methodologies for positive energy districts is taking place in Europe and Sweden. We identify three pitfalls that must be avoided so that positive energy districts meet their mitigation goals in the Swedish context. The goal of pushing out fossil fuels is not relevant in the current energy system, the mismatch between summer electricity production and winter energy demands should be addressed, and further implementations should consider collaboration with the established district heating grid.

Keywords: positive energy districts, energy system, renewable energy, European Union

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Authors: Eduardo Jorge Cabral dos Santos Fernandes

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The expression ‘Porto School’, usually associated with an educational institution, the School of Fine Arts of Porto, is applied for the first time with the sense of an architectural trend by Nuno Portas in a text published in 1983. The expression is used to characterize a set of works by Porto architects, in which common elements are found, namely the desire to reuse languages and forms of the German and Dutch rationalism of the twenties, using the work of Alvar Aalto as a mediation for the reinterpretation of these models. In the same year, Álvaro Siza classifies the Finnish architect as a miscegenation agent who transforms experienced models and introduces them to different realities in a text published in Jornal de Letras, Artes e Ideias. The influence of foreign models and their adaptation to the context has been a recurrent theme in Portuguese architecture, which finds important contributions in the writings of Alexandre Alves Costa, at this time. However, the identification of these characteristics in Siza’s work is not limited to the Portuguese theoretical production: it is the recognition of this attitude towards the context that leads Kenneth Frampton to include Siza in the restricted group of architects who embody Critical Regionalism (in his book Modern architecture: a critical history). For Frampton, his work focuses on the territory and on the consequences of the intervention in the context, viewing architecture as a tectonic fact rather than a series of scenographic episodes and emphasizing site-specific aspects (topography, light, climate). Therefore, the motto of this paper is the dichotomous opposition between foreign influences and adaptation to the context in the early work of Álvaro Siza (designed in the sixties) in which the influence (theoretical, methodological, and formal) of Alvar Aalto manifests itself in the form and the language: the pool at Quinta da Conceição, the Seaside Pools and the Tea House (three works in Leça da Palmeira) and the Lordelo Cooperative (in Porto). This work is part of a more comprehensive project, which considers several case studies throughout the Portuguese architect's vast career, built in Portugal and abroad, in order to obtain a holistic view.

Keywords: Alvar Aalto, Álvaro Siza, foreign influences, adaptation to the context

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Authors: Xinyuan Y. Song, Kai Kang

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Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

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