Search results for: Galileo new advanced features

Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Camilo Andres Agudelo-Velez, Lina María Martinez-Sanchez, Natalia Perilla-Hernandez, Maria De Los Angeles Rodriguez-Gazquez, Felipe Hernandez-Restrepo, Dayana Andrea Quintero-Moreno, Camilo Ruiz-Mejia, Isabel Cristina Ortiz-Trujillo, Monica Maria Zuluaga-Quintero

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Chronic obstructive pulmonary disease is common condition, characterized by a persistent blockage of airflow, partially reversible and progressive, that represents 5% of total deaths around the world, and it is expected to become the third leading cause of death by 2030. Objective: To establish the clinical and epidemiological profile of patients with chronic obstructive pulmonary disease in a medical institution from the city of Medellin, Colombia. Methods: A cross-sectional study was performed, with a sample of 50 patients with a diagnosis of chronic obstructive pulmonary disease in a private institution in Medellin, during 2015. The software SPSS vr. 20 was used for the statistical analysis. For the quantitative variables, averages, standard deviations, and maximun and minimun values were calculated, while for ordinal and nominal qualitative variables, proportions were estimated. Results: The average age was 73.5±9.3 years, 52% of the patients were women, 50% of them had retired, 46% ere married and 80% lived in the city of Medellín. The mean time of diagnosis was 7.8±1.3 years and 100% of the patients were treated at the internal medicine service. The most common clinical features were: 36% were classified as class D for the disease, 34% had a FEV1 <30%, 88% had a history of smoking and 52% had oxygen therapy at home. Conclusion: It was found that class D was the most common, and the majority of the patients had a history of smoking, indicating the need to strengthen promotion and prevention strategies in this regard.

Keywords: pulmonary disease, chronic obstructive, pulmonary medicine, oxygen inhalation therapy

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Authors: Andra-Iulia Ursa

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James Joyce employs several unconventional stylistic features in this landmark novel meant to experiment with language. The episode known as “Sirens” is entirely conceived around music and linguistic structures subordinated to sound. However, the aspiration to the condition of music is reflected throughout this entire literary work, as musical effects are echoed systematically. The numerous melodies scattered across the narrative play an important role in enhancing the thoughts and feelings that pass through the minds of the characters. Often the lyrics are distorted or interweaved with other words, preoccupations or memories, intensifying the stylistic effect. The Victorian song “Love’s old sweet song” is one of the most commonly referred to and meaningful musical allusions in Ulysses, becoming a leitmotif of infidelity. The lyrics of the song “M’appari”, from the opera “Martha”, are compared to an event from Molly and Bloom’s romantic history. Moreover, repeated phrases using words from “The bloom is on the rye” or “The croppy boy” serve as glances into the minds of the characters. Therefore, the central purpose of this study is to shed light on the way musical allusions flit through the episodes from the point of view of the stream of consciousness technique and to compare and analyse how these constructions are rendered into Romanian. Mircea Ivănescu, the single Romanian translator who succeeded in carrying out the translation of the entire ‘stylistic odyssey’, received both praises and disapprovals from the critics. This paper is not meant to call forth eventual flaws of the Romanian translation, but rather to elaborate the complexity of the task. Following an attentive examination and analysis of the two texts, from the point of view of form and meaning of the references to various songs, the conclusions of this study will be able to point out the intricacies of the process of translation.

Keywords: Joyce, melodious constructions, stream of consciousness, style, translation

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Authors: Renata Szewczyk, Beata Lachtara, Kinga Wieczorek, Jacek Osek

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Campylobacter is recognized as the main cause of bacterial gastrointestinal infections in Europe. A main source of the pathogen is poultry and poultry meat; however, other animals like pigs and cattle can also be reservoirs of the bacteria. Human Campylobacter infections are often self-limiting but in some cases, macrolide and fluoroquinolones have to be used. The aim of this study was to determine antimicrobial resistance patterns (AMR) of Campylobacter isolated from pig and cattle carcasses. Between July 2009 and December 2015, 735 swabs from pig (n = 457) and cattle (n = 278) carcasses were collected at Polish slaughterhouses. All samples were tested for the presence of Campylobacter by ISO 10272-1 and confirmed to species level using PCR. The antimicrobial susceptibility of Campylobacter isolates was determined by a microbroth dilution method with six antimicrobials: gentamicin (GEN), streptomycin (STR), erythromycin (ERY), nalidixic acid (NAL), ciprofloxacin (CIP) and tetracycline (TET). It was found that 167 of 735 samples (22.7%) were contaminated with Campylobacter. The vast majority of them were of pig origin (134; 80.2%), whereas for cattle carcasses Campylobacter was less prevalent (33; 19.8%). Among positive samples C. coli was predominant species (123; 73.7%) and it was isolated mainly from pig carcasses. The remaining isolates were identified as C. jejuni (44; 26.3%). Antimicrobial susceptibility indicated that 22 out of 167 Campylobacter (13.2%) were sensitive to all antimicrobials used. Fourteen of them were C. jejuni (63.6%; pig, n = 6; cattle, n = 8) and 8 was C. coli (36.4%; pig, n = 4; cattle, n = 4). Most of the Campylobacter isolates (145; 86.8%) were resistant to one or more antimicrobials (C. coli, n = 115; C. jejuni, n = 30). Comparing the AMR for Campylobacter species it was found that the most common pattern for C. jejuni was CIP-NAL-TET (9; 30.0%), whereas CIP-NAL-STR-TET was predominant among C. coli (47; 40.9%). Multiresistance, defined as resistance to three or more classes of antimicrobials, was found in 57 C. coli strains, mostly obtained from pig (52 isolates). On the other hand, only one C. jejuni strain, isolated from cattle, showed multiresistance with pattern CIP-NAL-STR-TET. Moreover, CIP-NAL-STR-TET was characteristic for most of multiresistant C. coli isolates (47; 82.5%). For the remaining C. coli the resistance patterns were CIP-ERY-NAL-TET (7 strains; 12.3%) and for one strain of each patterns: ERY-STR-TET, CIP-STR-TET, CIP-NAL-GEN-STR-TET. According to the present findings resistance to erythromycin was observed only in 11 C. coli (pig, n = 10; cattle, n = 1). In conclusion, the results of this study showed that pig carcasses may be a serious public health concern because of contamination with C. coli that might features multiresistance to antimicrobials.

Keywords: antimicrobial resistance, Campylobacter, carcasses, multi resistance

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Authors: M. A. Brown, K. Hugill, D. Meredith

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Since the establishment of midwifery, as a professional identity in its own right, in the early years of the 20th century, midwifery-led models of childbirth have prevailed in many parts of the world. However, in many locations midwives’ scope of practice remains underdeveloped or absent. In Qatar, all births take place in hospital and are under the professional jurisdiction of obstetricians, predominately supported by internationally trained nurse-midwives and obstetric nurses. The strategic vision for health services in Qatar endorsed a desire to provide women with the ‘Best Care Always’ and the introduction of midwifery was seen as a way to achieve this. In 2015 the process of recruiting postgraduate educated Clinical Midwife Specialists from international sources began. The midwives were brought together to initiate an in hospital and community service transformation plan. This plan set out a series of wide-ranging actions to transform maternity and neonatal services to make care safer and give women more health choices. Change in any organization is a complex and dynamic process. This is made even more complex when multifaceted professional and cross cultural factors are involved. This presentation reports upon the motivations and challenges that exist and the progress around introducing a multicultural midwifery model of childbirth care in the state of Qatar. The paper examines and reflects upon the drivers and unique features of childbirth in the country. Despite accomplishments, progress still needs to be made in order to fully implement sustainable changes to further improve care and ensure women and neonates get the ‘Best Care Always’. The progress within the transformation plan highlights how midwifery may coexist with competing models of maternity care to create an innovative, eclectic and culturally sensitive paradigm that can best serve women and neonatal health needs.

Keywords: culture, managing change, midwifery, neonatal, service transformation plan

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Authors: Elitsa Kolentsova, Dimitar Dimitrov, Vasko Idakiev, Tatyana Tabakova, Krasimir Ivanov

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Formaldehyde production by selective oxidation of methanol is an important industrial process. The main by-products in the waste gas are CO and dimethyl ether (DME). The idea of this study is to combine the advantages of both Cu-Mn and Cu-Co catalytic systems by obtaining a new mixed Cu-Mn-Co catalyst with high activity and selectivity at the simultaneous oxidation of CO, methanol, and DME. Two basic Cu-Mn samples with high activity were selected for further investigation: (i) manganese-rich Cu-Mn/γ–Al2O3 catalyst with Cu/Mn molar ratio 1:5 and (ii) copper-rich Cu-Mn/γ-Al2O3 catalyst with Cu/Mn molar ratio 2:1. Manganese in these samples was replaced by cobalt in the whole concentration region, and catalytic properties were determined. The results show a general trend of decreasing the activity toward DME oxidation and increasing the activity toward CO and methanol oxidation with the increase of cobalt up to 60% for both groups of catalyst. This general trend, however, contains specific features, depending on the composition of the catalyst and the nature of the oxidized gas. The catalytic activity of the sample with Cu/(Mn+Co) molar ratio of 2:1 is gradually changed with increasing the cobalt content. The activity of the sample with Cu/(Mn+Co) molar ratio of 1: 5 passes through a maximum at 60% manganese replacement by cobalt, probably due to the formation of highly dispersed Co-based spinel structures (Co3O4 and/or MnCo2O4). In conclusion, the present study demonstrates that the Cu-Mn-Co/γ–alumina supported catalysts have enhanced activity toward CO, methanol and DME oxidation. Cu/(Mn+Co) molar ratio 1:5 and Co/Mn molar ratio 1.5 in the active component can ensure successful oxidation of CO, CH3OH and DME. The active component of the mixed Cu-Mn-Co/γ–alumina catalysts consists of at least six compounds - CuO, Co3O4, MnO2, Cu1.5Mn1.5O4, MnCo2O4 and CuCo2O4, depending on the Cu/Mn/Co molar ratio. Chemical composition strongly influences catalytic properties, this effect being quite variable with regards to the different processes.

Keywords: Cu-Mn-Co catalysts, oxidation, carbon oxide, VOCs

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Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

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We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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Authors: Mohamed Boullouz, Mohamed Louay Metougui

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Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

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Authors: Tooran Tavangar, Masoud Hosseinpoor, Jeffrey S. Marshall, Ammar Yahia, Kamal Henri Khayat

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In this study, a four-way coupled CFD-DEM methodology was used to simulate the behavior of concrete pipe flow. Fresh concrete, characterized as a biphasic suspension, features aggregates comprising the solid-suspended phase with diverse particle-size distributions (PSD) within a non-Newtonian cement paste/mortar matrix forming the liquid phase. The fluid phase was simulated using CFD, while the aggregates were modeled using DEM. Interaction forces between the fluid and solid particles were considered through CFD-DEM computations. To capture the viscoelastic characteristics of the suspending fluid, a bi-viscous approach was adopted, incorporating a critical shear rate proportional to the yield stress of the mortar. In total, three diphasic suspensions were simulated, each featuring distinct particle size distributions and a concentration of 10% for five subclasses of spherical particles ranging from 1 to 17 mm in a suspending fluid. The adopted bi-viscous approach successfully simulated both un-sheared (plug flow) and sheared zones. Furthermore, shear-induced particle migration (SIPM) was assessed by examining coefficients of variation in particle concentration across the pipe. These SIPM values were then compared with results obtained using CFD-DEM under the Newtonian assumption. The study highlighted the crucial role of yield stress in the mortar phase, revealing that lower yield stress values can lead to increased flow rates and higher SIPM across the pipe.

Keywords: computational fluid dynamics, concrete pumping, coupled CFD-DEM, discrete element method, plug flow, shear-induced particle migration.

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Authors: Venkat S. Somayajula

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Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical features

Keywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle

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Authors: Tayyaba Azim, Bibi Amina

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The increase in the popularity of opinion mining with the rapid growth in the availability of social networks has attracted a lot of opportunities for research in the various domains of Sentiment Analysis and Natural Language Processing (NLP) using Artificial Intelligence approaches. The latest trend allows the public to actively use the internet for analyzing an individual’s opinion and explore the effectiveness of published facts. The main theme of this research is to account the public opinion on the most crucial and extensively discussed development projects, China Pakistan Economic Corridor (CPEC), considered as a game changer due to its promise of bringing economic prosperity to the region. So far, to the best of our knowledge, the theme of CPEC has not been analyzed for sentiment determination through the ML approach. This research aims to demonstrate the use of ML approaches to spontaneously analyze the public sentiment on Twitter tweets particularly about CPEC. Support Vector Machine SVM is used for classification task classifying tweets into positive, negative and neutral classes. Word2vec and TF-IDF features are used with the SVM model, a comparison of the trained model on manually labelled tweets and automatically generated lexicon is performed. The contributions of this work are: Development of a sentiment analysis system for public tweets on CPEC subject, construction of an automatic generation of the lexicon of public tweets on CPEC, different themes are identified among tweets and sentiments are assigned to each theme. It is worth noting that the applications of web mining that empower e-democracy by improving political transparency and public participation in decision making via social media have not been explored and practised in Pakistan region on CPEC yet.

Keywords: machine learning, natural language processing, sentiment analysis, support vector machine, Word2vec

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Authors: Oleg Redkin, Olga Bernikova

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Globalization and migrations have made cross-cultural contacts more frequent and intensive. Sometimes, these contacts may lead to misunderstanding between partners of communication and misinterpretations of the verbal messages that some researchers tend to consider as the 'clash of civilizations'. In most cases, reasons for that may be found in cultural and linguistic differences and hence misinterpretations of intentions and behavior. The current research examines factors of verbal and non-verbal communication that should be taken into consideration in verbal and non-verbal contacts. Language is one of the most important manifestations of the cultural code, and it is often considered as one of the special features of a civilization. The Arabic language, in particular, is commonly associated with Islam and the language and the Arab-Muslim civilization. It is one of the most important markers of self-identification for more than 200 million of native speakers. Arabic is the language of the Quran and hence the symbol of religious affiliation for more than one billion Muslims around the globe. Adequate interpretation of Arabic texts requires profound knowledge of its grammar, semantics of its vocabulary. Communicating sides who belong to different cultural groups are guided by different models of behavior and hierarchy of values, besides that the vocabulary each of them uses in the dialogue may convey different semantic realities and vary in connotations. In this context direct, literal translation in most cases cannot adequately convey the original meaning of the original message. Besides that peculiarities and diversities of the extralinguistic information, such as the body language, communicative etiquette, cultural background and religious affiliations may make the dialogue even more difficult. It is very likely that the so called 'clash of civilizations' in most cases is due to misinterpretation of counterpart's means of discourse such as language, cultural codes, and models of behavior rather than lies in basic contradictions between partners of communication. In the process of communication, one has to rely on universal values rather than focus on cultural or religious peculiarities, to take into account current linguistic and extralinguistic context.

Keywords: Arabic, civilization, discourse, language, linguistic

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Authors: Ahmed E. Hodaib, Mohamed A. Hashem

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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

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Authors: Mudassir Ghafoor, Irsalan Arif, Shuaib Salamat

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This paper presents modeling and analysis of different intake bump (compression surface) configurations and comparison with an existing supersonic aircraft having bump intake configuration. Many successful aircraft models have shown that Diverter less Supersonic Inlet (DSI) as compared to conventional intake can reduce weight, complexity and also maintenance cost. The research is divided into two parts. In the first part, four different intake bumps are modeled for comparative analysis keeping in view the consistency of outer perimeter dimensions of fighter aircraft and various characteristics such as flow behavior, boundary layer diversion and pressure recovery are analyzed. In the second part, modeled bumps are integrated with intake duct for performance analysis and comparison with existing supersonic aircraft data is carried out. The bumps are named as uniform large (Config 1), uniform small (Config 2), uniform sharp (Config 3), non-uniform (Config 4) based on their geometric features. Analysis is carried out at different Mach Numbers to analyze flow behavior in subsonic and supersonic regime. Flow behavior, boundary layer diversion and Pressure recovery are examined for each bump characteristics, and comparative study is carried out. The analysis reveals that at subsonic speed, Config 1 and Config 2 give similar pressure recoveries as diverterless supersonic intake, but difference in pressure recoveries becomes significant at supersonic speed. It was concluded from research that Config 1 gives better results as compared to Config 3. Also, higher amplitude (Config 1) is preferred over lower (Config 2 and 4). It was observed that maximum height of bump is preferred to be placed near cowl lip of intake duct.

Keywords: bump intake, boundary layer, computational fluid dynamics, diverter-less supersonic inlet

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Authors: Wahhaj Ahmed Farooqi, Bilal Ahmad, Sandra Maritza Zambrano Bernal

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In view of structural engineering, monitoring of structural responses over time is of great importance with respect to recent developments of construction technologies. Recently, developments of advanced computing tools have enabled researcher’s better execution of structural health monitoring (SHM) and control systems. In the last decade, building information modeling (BIM) has substantially enhanced the workflow of planning and operating engineering structures. Typically, building information can be stored and exchanged via model files that are based on the Industry Foundation Classes (IFC) standard. In this study a modeling approach for semantic modeling of SHM and control systems is integrated into the BIM methodology using the IFC standard. For validation of the modeling approach, a laboratory test structure, a four-story shear frame structure, is modeled using a conventional BIM software tool. An IFC schema extension is applied to describe information related to monitoring and control of a prototype SHM and control system installed on the laboratory test structure. The SHM and control system is described by a semantic model applying Unified Modeling Language (UML). Subsequently, the semantic model is mapped into the IFC schema. The test structure is composed of four aluminum slabs and plate-to-column connections are fully fixed. In the center of the top story, semi-active tuned liquid column damper (TLCD) is installed. The TLCD is used to reduce effects of structural responses in context of dynamic vibration and displacement. The wireless prototype SHM and control system is composed of wireless sensor nodes. For testing the SHM and control system, acceleration response is automatically recorded by the sensor nodes equipped with accelerometers and analyzed using embedded computing. As a result, SHM and control systems can be described within open BIM, dynamic responses and information of damages can be stored, documented, and exchanged on the formal basis of the IFC standard.

Keywords: structural health monitoring, open building information modeling, industry foundation classes, unified modeling language, semi-active tuned liquid column damper, nondestructive testing

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Authors: A. Mostaani, M. P. Pereira, B. F. Rolfe

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The increasing application of Advanced High Strength Steel (AHSS) in the automotive industry to fulfill crash requirements has introduced higher levels of wear in stamping dies and parts. Therefore, understanding wear behaviour in sheet metal forming is of great importance as it can help to reduce the high costs currently associated with tool wear. At the contact between the die and the sheet, the tips of hard tool asperities interact with the softer sheet material. Understanding the deformation that occurs during this interaction is important for our overall understanding of the wear mechanisms. For these reasons, the scratching of a perfectly plastic material by a rigid indenter has been widely examined in the literature; with finite element modelling (FEM) used in recent years to further understand the behaviour. The ‘wear mode diagram’ has been commonly used to classify the deformation regime of the soft work-piece during scratching, into three modes: ploughing, wedge formation, and cutting. This diagram, which is based on 2D slip line theory and upper bound method for perfectly plastic work-piece and rigid indenter, relates different wear modes to attack angle and interfacial strength. This diagram has been the basis for many wear studies and wear models to date. Additionally, it has been concluded that galling is most likely to occur during the wedge formation mode. However, there has been little analysis in the literature of how the material behaviour and deformation conditions associated with metal forming processes influence the wear behaviour. Therefore, the first aim of this work is first to use a commercial FEM package (Abaqus/Explicit) to build a 3D model to capture wear modes during scratching with indenters with different attack angles and different interfacial strengths. The second goal is to utilise the developed model to understand how wear modes might change in the presence of bulk deformation of the work-piece material as a result of the metal forming operation. Finally, the effect of the work-piece material properties, including strain hardening, will be examined to understand how these influence the wear modes and wear behaviour. The results show that both strain hardening and substrate deformation can change the critical attack angle at which the wedge formation regime is activated.

Keywords: finite element, pile-up, scratch test, wear mode

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Authors: Meghan E. Murray, Carri R. Tolmie

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This study aims to identify potential factors and widely applicable best practices that can contribute to improving corporate social responsibility (CSR) and corporate performance for firms by exploring the relationship between transformational leadership, spiritual intelligence, and emotional intelligence. Corporate social responsibility is when companies are cognizant of the impact of their actions on the economy, their communities, the environment, and the world as a whole while executing business practices accordingly. The prevalence of CSR has continuously strengthened over the past few years and is now a common practice in the business world, with such efforts coinciding with what stakeholders and the public now expect from corporations. Because of this, it is extremely important to be able to pinpoint factors and best practices that can improve CSR within corporations. One potential factor that may lead to improved CSR is spiritual intelligence (SQ), or the ability to recognize and live with a purpose larger than oneself. Spiritual intelligence is a measurable skill, just like emotional intelligence (EQ), and can be improved through purposeful and targeted coaching. This research project consists of two studies. Study 1 is a case study comparison of a benefit corporation and a non-benefit corporation. This study will examine the role of SQ and EQ as moderators in the relationship between the transformational leadership of employees within each company and the perception of each firm’s CSR and corporate performance. Project methodology includes creating and administering a survey comprised of multiple pre-established scales on transformational leadership, spiritual intelligence, emotional intelligence, CSR, and corporate performance. Multiple regression analysis will be used to extract significant findings from the collected data. Study 2 will dive deeper into spiritual intelligence itself by analyzing pre-existing data and identifying key relationships that may provide value to companies and their stakeholders. This will be done by performing multiple regression analysis on anonymized data provided by Deep Change, a company that has created an advanced, proprietary system to measure spiritual intelligence. Based on the results of both studies, this research aims to uncover best practices, including the unique contribution of spiritual intelligence, that can be utilized by organizations to help enhance their corporate social responsibility. If it is found that high spiritual and emotional intelligence can positively impact CSR effort, then corporations will have a tangible way to enhance their CSR: providing targeted employees with training and coaching to increase their SQ and EQ.

Keywords: corporate social responsibility, CSR, corporate performance, emotional intelligence, EQ, spiritual intelligence, SQ, transformational leadership

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Authors: Bülent Kantar, Numan Ünaldı

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This paper presents a new method which includes robust and invisible digital watermarking on images that is colored. Colored images are used as watermark. Frequency region is used for digital watermarking. Discrete wavelet transform and discrete stationary wavelet transform are used for frequency region transformation. Low, medium and high frequency coefficients are obtained by applying the two-level discrete wavelet transform to the original image. Low frequency coefficients are obtained by applying one level discrete stationary wavelet transform separately to all frequency coefficient of the two-level discrete wavelet transformation of the original image. For every low frequency coefficient obtained from one level discrete stationary wavelet transformation, watermarks are added. Watermarks are added to all frequency coefficients of two-level discrete wavelet transform. Totally, four watermarks are added to original image. In order to get back the watermark, the original and watermarked images are applied with two-level discrete wavelet transform and one level discrete stationary wavelet transform. The watermark is obtained from difference of the discrete stationary wavelet transform of the low frequency coefficients. A total of four watermarks are obtained from all frequency of two-level discrete wavelet transform. Obtained watermark results are compared with real watermark results, and a similarity result is obtained. A watermark is obtained from the highest similarity values. Proposed methods of watermarking are tested against attacks of the geometric and image processing. The results show that proposed watermarking method is robust and invisible. All features of frequencies of two level discrete wavelet transform watermarking are combined to get back the watermark from the watermarked image. Watermarks have been added to the image by converting the binary image. These operations provide us with better results in getting back the watermark from watermarked image by attacking of the geometric and image processing.

Keywords: watermarking, DWT, DSWT, copy right protection, RGB

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Authors: Rajashree Bothale, Venkateswara Rao

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Indian Himalayas also known as third pole with 0.9 Million SQ km area, contain the largest reserve of ice and snow outside poles and affect global climate and water availability in the perennial rivers. The variations in the extent of snow are indicative of climate change. The snow melt is sensitive to climate change (warming) and also an influencing factor to the climate change. A study of the spatio-temporal dynamics of snow cover and melt/freeze conditions is carried out using space based observations in visible and microwave bands. An analysis period of 2003 to 2015 is selected to identify and map the changes and trend in snow cover using Indian Remote Sensing (IRS) Advanced Wide Field Sensor (AWiFS) and Moderate Resolution Imaging Spectroradiometer(MODIS) data. For mapping of wet snow, microwave data is used, which is sensitive to the presence of liquid water in the snow. The present study uses Ku-band scatterometer data from QuikSCAT and Oceansat satellites. The enhanced resolution images at 2.25 km from the 13.6GHz sensor are used to analyze the backscatter response to dry and wet snow for the period of 2000-2013 using threshold method. The study area is divided into three major river basins namely Brahmaputra, Ganges and Indus which also represent the diversification in Himalayas as the Eastern Himalayas, Central Himalayas and Western Himalayas. Topographic variations across different zones show that a majority of the study area lies in 4000–5500 m elevation range and the maximum percent of high elevated areas (>5500 m) lies in Western Himalayas. The effect of climate change could be seen in the extent of snow cover and also on the melt/freeze status in different parts of Himalayas. Melt onset day increases from east (March11+11) to west (May12+15) with large variation in number of melt days. Western Himalayas has shorter melt duration (120+15) in comparison to Eastern Himalayas (150+16) providing lesser time for melt. Eastern Himalaya glaciers are prone for enhanced melt due to large melt duration. The extent of snow cover coupled with the status of melt/freeze indicating solar radiation can be used as precursor for monsoon prediction.

Keywords: Indian Himalaya, Scatterometer, Snow Melt/Freeze, AWiFS, Cryosphere

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Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

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The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

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Authors: Xianping Du, Runlu Miao, Guanjun Zhang, Libo Cao, Feng Zhu

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Current vehicle safety standards and human body injury criteria were established based on the biomechanical response of Euro-American human body, without considering the difference in the body anthropometry and injury characteristics among different races, particularly the East Asian people with smaller body size. Absence of such race specific design considerations will negatively influence the protective performance of safety products for these populations, and weaken the accuracy of injury thresholds derived. To resolve these issues, in this study, we aim to develop a race specific finite element model to simulate the impact response of the lower extremity of a 50th percentile East Asian (Chinese) male. The model was built based on medical images for the leg of an average size Chinese male and slightly adjusted based on the statistical data. The model includes detailed anatomic features and is able to simulate the muscle active force. Thirteen biomechanical tests available in the literature were used to validate its biofidelity. Using the validated model, a pedestrian-car impact accident taking place in China was re-constructed computationally. The results show that the newly developed lower leg model has a good performance in predicting dynamic response and tibia fracture pattern. An additional comparison on the fracture tolerance of the East Asian and Euro-American lower limb suggests that the current injury criterion underestimates the degree of injury of East Asian human body.

Keywords: lower limb, East Asian body characteristics, traffic accident reconstruction, finite element analysis, injury tolerance

Procedia PDF Downloads 274

Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Mansoor Soomro

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The evolution of power electronic equipment has been pivotal in making industrial processes productive, efficient and safe. Despite its attractive features, it has been due to nonlinear loads which make it vulnerable to power quality conditions. Harmonics is one of the power quality problem in which the harmonic frequency is integral multiple of supply frequency. Therefore, the supply voltage and supply frequency do not last within their tolerable limits. As a result, distorted current and voltage waveform may appear. Attributes of low power quality confirm that an electrical device or equipment is likely to malfunction, fail promptly or unable to operate under all applied conditions. The electrical power system is designed for delivering power reliably, namely maximizing power availability to customers. However, power quality events are largely untracked, and as a result, can take out a process as many as 20 to 30 times a year, costing utilities, customers and suppliers of load equipment, a loss of millions of dollars. The ill effects of current harmonics reduce system efficiency, cause overheating of connected equipment, result increase in electrical power and air conditioning costs. With the passage of time and the rapid growth of power electronic converters has highlighted the damages of current harmonics in the electrical power system. Therefore, it has become essential to address the bad influence of current harmonics while planning any suitable changes in the electrical installations. In this paper, an effort has been made to mitigate the effects of dominant 3rd order current harmonics. Passive filtering technique with six pulse multiplication converter has been employed to mitigate them. Since, the standards of power quality are to maintain the supply voltage and supply current within certain prescribed standard limits. For this purpose, the obtained results are validated as per specifications of IEEE 519-1992 and IEEE 519-2014 performance standards.

Keywords: current harmonics, power quality, passive filters, power electronic converters

Procedia PDF Downloads 287

Authors: Justin Nwabanne, Sam Omenyi, Jeremiah Chukwuneke

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This work presents structural nonlinear static analysis of a horizontal taut cable using Finite Element Analysis (FEA) method. The FEA was performed analytically to determine the tensions at each nodal point and subsequently, performed based on finite element displacement method computationally using the FEA software, ANSYS 14.0 to determine their behaviour under the influence of aerodynamic forces imposed on the cable. The convergence procedure is adapted into the method to prevent excessive displacements through the computations. The work compared the two FEA cases by examining the effectiveness of the analytical model in describing the response with few degrees of freedom and the ability of the nonlinear finite element procedure adopted to capture the complex features of cable dynamics with reference to the aerodynamic external influence. Results obtained from this work explain that the analytic FEM results without aerodynamic influence show a parabolic response with an optimum deflection at nodal points 12 and 13 with the cable weight at nodes 12 and 13 having the value -1.002936N while for the cable tension shows an optimum deflection value for nodes 12 and 13 at -189396.97kg/km. The maximum displacement for the cable system was obtained from ANSYS 14.0 as 4483.83 mm for X, Y and Z components of displacements at node number 2 while the maximum displacement obtained is 4218.75mm for all the directional components. The dynamic behaviour of a taut cable investigated has application in a typical power transmission line. Aerodynamic influences on the cables were considered using FEA approach by employing ANSYS 14.0 showed a complex modal behaviour as expected.

Keywords: aerodynamics, cable tension and weight, finite element analysis, nodal, non-linear model, optimum deflection, suspended cable, transmission line

Procedia PDF Downloads 264

Authors: Saeeda Batool, Ather Maqsood Ahmed

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This study investigates the impact of public healthcare facilities and socio-economic circumstances on the status of child health in Pakistan. The complete analysis is carried out in correspondence with fourth and sixth millennium development goals. Further, the health variables chosen are also inherited from targeted indicators of the mentioned goals (MDGs). Trends in the Human Opportunity Index (HOI) for both health inequalities and coverage are analyzed using the Pakistan Social and Living Standards Measurement (PLSM) data set for 2001-02 to 2012-13 at the national and provincial level. To reveal the relative importance of each circumstance in achieving the targeted values for child health, Shorrocks decomposition is applied on HOI. The annual point average growth rate of HOI is used to simulate the time period for the achievement of target set by MDGs and universal access also. The results indicate an improvement in HOI for a reduction in child mortality rates from 52.1% in 2001-02 to 67.3% in 2012-13, which confirms the availability of healthcare opportunities to a larger segment of society. Similarly, immunization against measles and other diseases such as Diphtheria, Polio, Bacillus Calmette-Guerin (BCG), and Hepatitis has also registered an improvement from 51.6% to 69.9% during the period of study at the national level. On a positive note, no gender disparity has been found for child health indicators and that health outcome is mostly affected by the parental and geographical features and availability of health infrastructure. However, the study finds that this achievement has been uneven across provinces. Pakistan is not only lagging behind in achieving its health goals, disappointingly with the current rate of health care provision, but it will take many additional years to achieve its targets.

Keywords: socio-economic circumstances, unmet MDGs, public healthcare services, child and infant mortality

Procedia PDF Downloads 212

Authors: Aymen Laadhari

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During the last decade, an increasing number of contributions have been made in the fields of scientific computing and numerical methodologies applied to the study of the hemodynamics in the heart. In contrast, the numerical aspects concerning the interaction of pulsatile blood flow with highly deformable thin leaflets have been much less explored. This coupled problem remains extremely challenging and numerical difficulties include e.g. the resolution of full Fluid-Structure Interaction problem with large deformations of extremely thin leaflets, substantial mesh deformations, high transvalvular pressure discontinuities, contact between leaflets. Although the Lagrangian description of the structural motion and strain measures is naturally used, many numerical complexities can arise when studying large deformations of thin structures. Eulerian approaches represent a promising alternative to readily model large deformations and handle contact issues. We present a fully Eulerian finite element methodology tailored for the simulation of pulsatile blood flow in the aorta and sinus of Valsalva interacting with highly deformable thin leaflets. Our method enables to use a fluid solver on a fixed mesh, whilst being able to easily model the mechanical properties of the valve. We introduce a semi-implicit time integration scheme based on a consistent NewtonRaphson linearization. A variant of the classical Newton method is introduced and guarantees a third-order convergence. High-fidelity computational geometries are built and simulations are performed under physiological conditions. We address in detail the main features of the proposed method, and we report several experiments with the aim of illustrating its accuracy and efficiency.

Keywords: eulerian, level set, newton, valve

Procedia PDF Downloads 264

Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

Procedia PDF Downloads 126

Authors: Iman Jabbar

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Within the scope of professionalism and in order to compete with the modern world, teachers, are expected to develop their teaching skills and activities in addition to their professional knowledge. At the college level, the teacher should be able to face classroom challenges through his engagement with the learning situation to understand the students and their needs. In our field of TESOL, the role of the English teacher is no longer restricted to teaching English texts, but rather he should endeavor to enhance the students’ skills such as communication and critical analysis. Within the literature of professionalism, there are certain strategies and tools that an English teacher should adopt to develop his competence and performance. Reflective practice, which is an exploratory process, is one of these strategies. Another strategy contributing to classroom development is motivation. It is crucial in students’ learning as it affects the quality of learning English in the classroom in addition to determining success or failure as well as language achievement. This is a qualitative study grounded on interpretive perspectives of teachers and students regarding the process of professional development. This study aims at (a) understanding how teachers at the college level conceptualize reflective practice and motivation inside EFL classroom, and (b) exploring the methods and strategies that they implement to practice reflection and motivation. This study and is based on two questions: 1. How do EFL teachers perceive and view reflection and motivation in relation to their teaching and professional development? 2. How can reflective practice and motivation be developed into practical strategies and actions in EFL teachers’ professional context? The study is organized into two parts, theoretical and practical. The theoretical part reviews the literature on the concept of reflective practice and motivation in relation to professional development through providing certain definitions, theoretical models, and strategies. The practical part draws on the theoretical one, however; it is the core of the study since it deals with two issues. It involves the research design, methodology, and methods of data collection, sampling, and data analysis. It ends up with an overall discussion of findings and the researcher's reflections on the investigated topic. In terms of significance, the study is intended to contribute to the field of TESOL at the academic level through the selection of the topic and investigating it from theoretical and practical perspectives. Professional development is the path that leads to enhancing the quality of teaching English as a foreign or second language in a way that suits the modern trends of globalization and advanced technology.

Keywords: professional development, motivation, reflection, learning

Procedia PDF Downloads 431

Authors: Hernan Arturo Blas López, Gustavo Henndel Lopes, Antonio Carlos Silva Costa Teixeira, Carmen Elena Flores Barreda, Patricia Araujo Pantoja

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Phenols are toxic for life and the environment and may come from many sources. Uncured phenolic monomers present in phenolic resins used as binders in grinding wheels and emery paper can contaminate industrial wastewaters in abrasives manufacture plants. Furthermore, vestiges of resol and novolacs resins generated by wear and tear of abrasives are also possible sources of water contamination by phenolics in these facilities. Fortunately, advanced oxidation by dark Fenton and photo-Fenton techniques are capable of oxidizing phenols and their degradation products up to their mineralization into H₂O and CO₂. The maximal allowable concentrations for phenols in Peruvian waterbodies is very low, such that insufficiently treated effluents from the abrasives industry are a potential environmental noncompliance. The current case study highlights findings obtained during the lab-scale application of Fenton’s and photo-assisted Fenton’s chemistries to real industrial wastewater samples from an abrasives manufacture plant in Peru. The goal was to reduce the phenolic content and sample toxicity. For this purpose, two independent variables-reaction time and effect of ultraviolet radiation–were studied as for their impacts on the concentration of total phenols, total organic carbon (TOC), biological oxygen demand (BOD) and chemical oxygen demand (COD). In this study, diluted samples (1 L) of the industrial effluent were treated with Fenton’s reagent (H₂O₂ and Fe²⁺ from FeSO₄.H₂O) during 10 min in a photochemical batch reactor (Alphatec RFS-500, Brazil) at pH 2.92. In the case of photo-Fenton tests with ultraviolet lamps of 9 W, UV-A, UV-B and UV-C lamps were evaluated. All process conditions achieved 100% of phenols degraded within 5 minutes. TOC, BOD and COD decreased by 49%, 52% and 86% respectively (all processes together). However, Fenton treatment was not capable of reducing BOD, COD and TOC below a certain value even after 10 minutes, contrarily to photo-Fenton. It was also possible to conclude that the processes here studied degrade other compounds in addition to phenols, what is an advantage. In all cases, elevated effluent dilution factors and high amounts of oxidant agent impact negatively the overall economy of the processes here investigated.

Keywords: fenton oxidation, wastewater treatment, phenols, abrasives industry

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Authors: Safieh Javadinejad

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In order to make well-informed decisions respecting long-term system planning, resource managers and policy creators necessitate to comprehend the interconnections among energy and water utilization and manufacture—and also the energy-water nexus. Planning and assessment issues contain the enhancement of strategies for declining the water and energy system’s vulnerabilities to climate alteration with also emissions of decreasing greenhouse gas. In order to deliver beneficial decision support for climate adjustment policy and planning, understanding the regionally-specific features of the energy-water nexus, and the history-future of the water and energy source systems serving is essential. It will be helpful for decision makers understand the nature of current water-energy system conditions and capacity for adaptation plans for future. This research shows an integrated hydrology/energy modeling platform which is able to extend water-energy examines based on a detailed illustration of local circumstances. The modeling links the Water Evaluation and Planning (WEAP) and the Long Range Energy Alternatives Planning (LEAP) system to create full picture of water-energy processes. This will allow water managers and policy-decision makers to simply understand links between energy system improvements and hydrological processing and realize how future climate change will effect on water-energy systems. The Zayandeh Rud river basin in Iran is selected as a case study to show the results and application of the analysis. This region is known as an area with large integration of both the electric power and water sectors. The linkages between water, energy and climate change and possible adaptation strategies are described along with early insights from applications of the integration modeling system.

Keywords: climate impacts, hydrology, water systems, adaptation planning, electricity, integrated modeling

Procedia PDF Downloads 271