Search results for: cloud based

Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

Procedia PDF Downloads 123

Authors: Jean Paul M. Milambo

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Purpose: Aromatase inhibitors (AIs) are indicated in the treatment of hormone-receptive breast cancer in postmenopausal women in various settings. Studies have shown cardiovascular events in some developed countries. To date the data is sparce for evidence-based recommendations in African clinical settings due to lack of cancer registries, capacity building and surveillance systems. Therefore, this study was conducted to assess the feasibility of HyBeacon® probe genotyping adjunctive to standard care for timely prediction and diagnosis of Aromatase inhibitors (AIs) associated adverse events in breast cancer survivors in Africa. Methods: Cross sectional study was conducted to assess the knowledge of POCT among six African countries using online survey and telephonically contacted. Incremental cost effectiveness ratio (ICER) was calculated, using diagnostic accuracy study. This was based on mathematical modeling. Results: One hundred twenty-six participants were considered for analysis (mean age = 61 years; SD = 7.11 years; 95%CI: 60-62 years). Comparison of genotyping from HyBeacon® probe technology to Sanger sequencing showed that sensitivity was reported at 99% (95% CI: 94.55% to 99.97%), specificity at 89.44% (95% CI: 87.25 to 91.38%), PPV at 51% (95%: 43.77 to 58.26%), and NPV at 99.88% (95% CI: 99.31 to 100.00%). Based on the mathematical model, the assumptions revealed that ICER was R7 044.55. Conclusion: POCT using HyBeacon® probe genotyping for AI-associated adverse events maybe cost effective in many African clinical settings. Integration of preventive measures for early detection and prevention guided by different subtype of breast cancer diagnosis with specific clinical, biomedical and genetic screenings may improve cancer survivorship. Feasibility of POCT was demonstrated but the implementation could be achieved by improving the integration of POCT within primary health cares, referral cancer hospitals with capacity building activities at different level of health systems. This finding is pertinent for a future envisioned implementation and global scale-up of POCT-based initiative as part of risk communication strategies with clear management pathways.

Keywords: breast cancer, diagnosis, point of care, South Africa, aromatase inhibitors

Procedia PDF Downloads 62

Authors: Lamia L. G. Al-Mahamad, Benjamin R. Horrocks, Andrew Houlton

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Hydrogels based on metal coordination polymers of nucleosides and a range of metal ions (Au, Ag, Cu) have been prepared and characterized by atomic force microscopy (AFM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, ultraviolet-visible absorption spectroscopy, and powder X-ray diffraction. AFM images of the xerogels revealed the formation of extremely long polymer molecules (> 10 micrometers, the maximum scan range). This result is also consistent with TEM images which show a fibrous morphology. Oxidative doping of the Au-nucleoside fibres produces an electrically conductive nanowire. No sharp Bragg peaks were found at the at the X-ray diffraction pattern for metal ions hydrogels indicating that the samples were amorphous, but instead the data showed broad peaks in the range 20 < Q < 40 and correspond to distances d=2μ/Q. The data was analysed using a simplified Rietveld method by fitting a regression model to obtain the distance between atoms.

Keywords: hydrogel, metal ions, nanowire, nucleoside

Procedia PDF Downloads 246

Authors: Ruoyu Mao

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Exploring the relationship between urban green development and regional integration level is of great significance for realising regional high quality and sustainable development. Based on the Tapio decoupling model and the theoretical framework of urban green development and regional integration, this paper builds an analysis system, makes a quantitative analysis of urban green development and regional integration level in a certain period, and discusses the relationship between the two. It also takes China's Yangtze River Delta urban agglomeration as an example to study the degree of decoupling, the type of decoupling, and the trend of the evolution of the spatio-temporal pattern of decoupling between the level of urban green development and the level of regional integration in the period of 2014-2021, with the aim of providing a useful reference for the future development of the region.

Keywords: regional integration, urban green development, Tapio decoupling model, Yangtze River Delta urban agglomeration

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Authors: Li Xu, Yang Hong, T. Zhao Wen

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Experimental results of many RC beam-column subassemblage indicate that slippage of longitudinal beam rebar within the joint and the shear deformation of joint core have significant influence on seismic behavior of the subassemblage. However, rigid joint assumption has been generally used in the seismic response analysis of RC frames, in which two kinds of inelastic deformation of joint have been ignored. Based on OpenSees platform, ‘Super Joint Element Model’ with more detailed inelastic mechanism is used to simulate the inelastic response of joints. Two finite element models of typical RC plane frame, namely considering or ignoring the inelastic deformation of joint respectively, were established and analyzed under seven strong earthquake waves. The simulated global and local inelastic deformations of the RC plane frame is shown and discussed. The analyses also confirm the security of the earthquake-resistant frame designed according to Chinese codes.

Keywords: frame structure, beam-column joint, longitudinal bar slippage, shear deformation, nonlinear analysis

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Authors: N. K. Thakur

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A major proportion of the formations drilled for the production of hydrocarbons consists of clay containing shales. The petroleum industry has hugely investigated the role of clay minerals and their subsequent effect on wellbore stability during the drilling and production of hydrocarbons. It has been found that when the shale formation comes in contact with water-based drilling fluid, the interaction of clay minerals like montmorillonite with infiltrated water leads to hydration of the clay minerals, which causes shale swelling. When shale swelling proceeds further, it may lead to major drilling complications like caving, pipe sticking, which invariably influences wellbore stability, wellbore diameter, the mechanical strength of shale, stress distribution in the wellbore, etc. These problems ultimately lead to an increase in nonproductive time and additional costs during drilling. Several additives are used to prevent shale instability. Among the popular additives used for shale inhibition in drilling muds, ionic liquids and nanoparticles are emerging to be the best additives. The efficiency of the proposed additives will be studied and compared with conventional clay inhibitors like KCl. The main objective is to develop a highly efficient water-based mud for mitigating shale instability and reducing fluid loss which is environmentally friendly and does not alter the formation permeability. The use of nanoparticles has been exploited to enhance the rheological and fluid loss properties in water-based drilling fluid ionic liquid have attracted significant research interest due to its unique thermal stability. It is referred to as ‘green chemical’. The preliminary experimental studies performed are promising. The application of more effective mud additives is always desirable to make the drilling process techno-economically proficient.

Keywords: ionic liquid, shale inhibitor, wellbore stability, unconventional

Procedia PDF Downloads 171

Authors: Hafida Bouarfa, Mohamed Abed

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The main object of our work is the development and the validation of a system indicated Fuzzy Vulnerability. Fuzzy Vulnerability uses a fuzzy representation in order to tolerate the imprecision during the description of construction. At the the second phase, we evaluated the similarity between the vulnerability of a new construction and those of the whole of the historical cases. This similarity is evaluated on two levels: 1) individual similarity: bases on the fuzzy techniques of aggregation; 2) Global similarity: uses the increasing monotonous linguistic quantifiers (RIM) to combine the various individual similarities between two constructions. The third phase of the process of Fuzzy Vulnerability consists in using vulnerabilities of historical constructions narrowly similar to current construction to deduce its estimate vulnerability. We validated our system by using 50 cases. We evaluated the performances of Fuzzy Vulnerability on the basis of two basic criteria, the precision of the estimates and the tolerance of the imprecision along the process of estimation. The comparison was done with estimates made by tiresome and long models. The results are satisfactory.

Keywords: case based reasoning, fuzzy logic, fuzzy case based reasoning, seismic vulnerability

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Authors: Isa Ahmadi, Ramin Khamedi

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In this paper, the elasto-plastic and cyclic torsion of a shaft is studied using a finite element method. The Prager kinematic hardening theory of plasticity with the Ramberg and Osgood stress-strain equation is used to evaluate the cyclic loading behavior of the shaft under the torsional loading. The material of shaft is assumed to follow the non-linear strain hardening property based on the Prager model. The finite element method with C1 continuity is developed and used for solution of the governing equations of the problem. The successive substitution iterative method is used to calculate the distribution of stresses and plastic strains in the shaft due to cyclic loads. The shear stress, effective stress, residual stress and elastic and plastic shear strain distribution are presented in the numerical results.

Keywords: cyclic loading, finite element analysis, Prager kinematic hardening model, torsion of shaft

Procedia PDF Downloads 395

Authors: Luh Eka Suryani, Purhadi

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Poisson regression is a non-linear regression model with response variable in the form of count data that follows Poisson distribution. Modeling for a pair of count data that show high correlation can be analyzed by Poisson Bivariate Regression. Data, the number of infant mortality and maternal mortality, are count data that can be analyzed by Poisson Bivariate Regression. The Poisson regression assumption is an equidispersion where the mean and variance values are equal. However, the actual count data has a variance value which can be greater or less than the mean value (overdispersion and underdispersion). Violations of this assumption can be overcome by applying Generalized Poisson Regression. Characteristics of each regency can affect the number of cases occurred. This issue can be overcome by spatial analysis called geographically weighted regression. This study analyzes the number of infant mortality and maternal mortality based on conditions in East Java in 2016 using Geographically Weighted Bivariate Generalized Poisson Regression (GWBGPR) method. Modeling is done with adaptive bisquare Kernel weighting which produces 3 regency groups based on infant mortality rate and 5 regency groups based on maternal mortality rate. Variables that significantly influence the number of infant and maternal mortality are the percentages of pregnant women visit health workers at least 4 times during pregnancy, pregnant women get Fe3 tablets, obstetric complication handled, clean household and healthy behavior, and married women with the first marriage age under 18 years.

Keywords: adaptive bisquare kernel, GWBGPR, infant mortality, maternal mortality, overdispersion

Procedia PDF Downloads 145

Authors: Shahnam Behnam Malekzadeh, Ian Kerr, Tyson Kaempffer, Teague Harper, Andrew Watson

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The Site C Hydroelectric dam is currently being constructed in north-eastern British Columbia on sub-horizontal sedimentary strata that dip approximately 15 meters from one bank of the Peace River to the other. More than 615 pressure sensors (Vibrating Wire Piezometers) have been installed on bedding planes (BPs) since construction began, with over 80 more planned before project completion. These pressure measurements are essential to monitor the stability of the rock foundation during and after construction and for dam safety purposes. BPs are identified by their clay gouge infilling, which varies in thickness from less than 1 to 20 mm and can be challenging to identify as the core drilling process often disturbs or washes away the gouge material. Without the use of depth predictions from nearby boreholes, stratigraphic markers, and downhole geophysical data, it is difficult to confidently identify BP targets for the sensors. In this paper, a Case-Based Reasoning (CBR) method was used to develop an empirical model called the Bedding Plane Elevation Prediction (BPEP) to help geologists and geotechnical engineers to predict geological features and bedding planes at new locations in a fast and accurate manner. To develop CBR, a database was developed based on 64 pressure sensors already installed on key bedding planes BP25, BP28, and BP31 on the Right Bank, including bedding plane elevations and coordinates. Thirteen (20%) of the most recent cases were selected to validate and evaluate the accuracy of the developed model, while the similarity was defined as the distance between previous cases and recent cases to predict the depth of significant BPs. The average difference between actual BP elevations and predicted elevations for above BPs was ±55cm, while the actual results showed that 69% of predicted elevations were within ±79 cm of actual BP elevations while 100% of predicted elevations for new cases were within ±99cm range. Eventually, the actual results will be used to develop the database and improve BPEP to perform as a learning machine to predict more accurate BP elevations for future sensor installations.

Keywords: case-based reasoning, geological feature, geology, piezometer, pressure sensor, core logging, dam construction

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Authors: Maximilian Cedzich, Ingo Dietz Von Bayer, Roland Jochem

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In order for industrial companies to continue to succeed in dynamic, globalized markets, they must be able to train their employees in an agile manner and at short notice in line with the exogenous conditions that arise. For this purpose, it is indispensable to operate a proactive competence management system for employees that recognizes qualification needs timely in order to be able to address them promptly through qualification measures. However, there are hardly any approaches to be found in the literature that includes systematic, proactive competence management. In order to help close this gap, this publication presents a process model that systematically develops bottom-up, future-oriented target competence profiles based on the tasks of the employees. Concretely, in the first step, the tasks of the individual employees are examined for assumed future conditions. In other words, qualitative scenarios are considered for the individual tasks to determine how they are likely to change. In a second step, these scenario-based future tasks are translated into individual future-related target competencies of the employee using a matrix of generic task properties. The final step pursues the goal of validating the target competence profiles formed in this way within the framework of a management workshop. This process model provides industrial companies with a tool that they can use to determine the competencies required by their own employees in the future and compare them with the actual prevailing competencies. If gaps are identified between the target and the actual, these qualification requirements can be closed in the short term by means of qualification measures.

Keywords: dynamic globalized markets, employee competence management, industrial companies, knowledge management

Procedia PDF Downloads 180

Authors: Najla Althuniyan

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Online discussions take place across different platforms. These discussions have the potential to extract crowd wisdom and capture the collective intelligence from a different perspective. However, certain phenomena, such as controversy, often appear in online argumentation that makes the discussion between participants heated. Heated discussions can be used to extract new knowledge. Therefore, detecting the presence of controversy is an essential task to determine if collective intelligence can be extracted from online discussions. This paper uses existing measures for estimating controversy quantitatively in cyber-argumentation. First, it defines controversy in different fields, and then it identifies the attributes of controversy in online discussions. The distributions of user opinions and the distance between opinions are used to calculate the controversial degree of a discussion. Finally, the results from each controversy measure are discussed and analyzed using an empirical study generated by a cyber-argumentation tool. This is an improvement over the existing measurements because it does not require ground-truth data or specific settings and can be adapted to distribution-based or distance-based opinions.

Keywords: online argumentation, controversy, collective intelligence, agreement analysis, collaborative decision-making, fuzzy logic

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Authors: Davide Forcellini

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The most recent development of earthquake engineering is based on concept of design consisting in prescribed performance rather than the more traditional prescriptive approaches. The paper aims to assess the effects of isolation devices and soil structure interaction on a benchmark bridge adopting a Performance-Based Earthquake Engineering methodology. Several isolated configurations of abutments and pier connections are compared performing the most representative isolation devices. Isolation systems suitability depends on many factors, mainly connected with ground effects. In this regard, the second purpose of this paper is to assess the effects of soil-structure interaction (SSI) on the studied bridge configurations. Contributions of isolation technique and soil structure interaction are assessed evaluating the resistance effects applied to Peak Ground Acceleration (PGA) levels in terms of cost and time repair quantities.

Keywords: base isolation, bridge, earthquake engineering, non linearity, PBEE methodology, seismic assessment, soil structure interaction

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Authors: Ghada S. Moussa

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With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management. This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.

Keywords: appearance attributes, geometric attributes, support vector machine, vehicle classification

Procedia PDF Downloads 324

Authors: Zainab Almukhtar, Adel Merabet

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In this paper, a method for maximum power point tracking of a photovoltaic energy conversion system is presented. This method is based on using the difference between the power from the solar panel and an estimated power value to control the DC-DC converter of the photovoltaic system. The difference is continuously compared with a preset error permitted value. If the power difference is more than the error, the estimated power is multiplied by a factor and the operation is repeated until the difference is less or equal to the threshold error. The difference in power will be used to trigger a DC-DC boost converter in order to raise the voltage to where the maximum power point is achieved. The proposed method was experimentally verified through a PV energy conversion system driven by the OPAL-RT real time controller. The method was tested on varying radiation conditions and load requirements, and the Photovoltaic Panel was operated at its maximum power in different conditions of irradiation.

Keywords: control system, error, solar panel, MPPT tracking

Procedia PDF Downloads 256

Authors: Hela Ben Maallem

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Applications based on virtual reality offer many benefits to the heritage and tourism sector. Digital heritage mediation is a constantly emerging field that aims to reconstruct the history of heritage items and sites while at the same time highlighting the identity of a community or region and encouraging public engagement. This research focuses on the analysis of a virtual reality application used in a heritage digital mediation project. The modality introduced is examined through a case study of the Djerba View VR application. The aim of this study is to understand the nature and potential uses of this immersive technology and to focus on the study of the possibilities of this medium. The goal of this article is to analyze how 3D reconstruction and immersive storytelling can offer an immersive, interactive and engaging user experience while meeting the expectations and needs of visitors in a context of technological transition and user-centered design.

Keywords: digital heritage mediation, user centered design, immersive storytelling, user experience, interactivity

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Authors: Ali Dulla

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This paper introduces a new dataset (and the methodology used to generate it) based on a wide range of historical Arabic documents containing clean data simple and homogeneous-page layouts. The experiments are implemented on printed and handwritten documents obtained respectively from some important libraries such as Qatar Digital Library, the British Library and the Library of Congress. We have gathered and commented on 150 archival document images from different locations and time periods. It is based on different documents from the 17th-19th century. The dataset comprises differing page layouts and degradations that challenge text line segmentation methods. Ground truth is produced using the Aletheia tool by PRImA and stored in an XML representation, in the PAGE (Page Analysis and Ground truth Elements) format. The dataset presented will be easily available to researchers world-wide for research into the obstacles facing various historical Arabic documents such as geometric correction of historical Arabic documents.

Keywords: dataset production, ground truth production, historical documents, arbitrary warping, geometric correction

Procedia PDF Downloads 153

Authors: Fuad Ali Mohammed Al-Yarimi

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Many algorithms have been proposed to provide privacy preserving in data mining. These protocols are based on two main approaches named as: the perturbation approach and the Cryptographic approach. The first one is based on perturbation of the valuable information while the second one uses cryptographic techniques. The perturbation approach is much more efficient with reduced accuracy while the cryptographic approach can provide solutions with perfect accuracy. However, the cryptographic approach is a much slower method and requires considerable computation and communication overhead. In this paper, a new scalable protocol is proposed which combines the advantages of the perturbation and distortion along with cryptographic approach to perform privacy preserving in distributed frequent itemset mining on horizontally distributed data. Both the privacy and performance characteristics of the proposed protocol are studied empirically.

Keywords: anonymity data, data mining, distributed frequent itemset mining, gaussian perturbation, perturbation approach, privacy preserving data mining

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Authors: Dalila Hammiche, Lisa Klaai, Sonia Imzi, Amar Boukerrou

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The fight against plastic pollution implies the development of polymers as alternatives to synthetic polymers. Starch is a natural polymer that can easily be plasticized by means of additives. The objective of this work is to develop and characterize biodegradable biofilms based on starch, plasticized by glycerol (20 and 30%). The elaboration of the biofilms was carried out by the casting method under simple conditions. The samples were characterized by infrared spectroscopy analysis with Fourier transform (FTIR), thermogravimetric analysis, and biodegradability test. Infrared spectral analysis showed that the 30% and 20% glycerol films have the same chemical structure and no functional group changes occurred. Thermogravimetric analysis showed that a 30% glycerol film has higher thermal stability than a 20% glycerol film. Biodegradability test showed that the lower the percentage of glycerol, the more easily the biofilm degrades.

Keywords: starch, natural sources, FTIR, thermogravimetric analysis, biodegradability test

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Authors: S. Fröhlich, M. Herold, M. Allmer

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Early stage quantitative analysis of host cell protein (HCP) variations is challenging yet necessary for comprehensive bioprocess development. High resolution mass spectrometry (HRMS) provides a high-end technology for accurate identification alongside with quantitative information. Hereby we describe a flexible HRMS assay platform to quantify HCPs relevant in microbial expression systems such as E. Coli in both up and downstream development by means of MVDA tools. Cell pellets were lysed and proteins extracted, purified samples not further treated before applying the SMART tryptic digest kit. Peptides separation was optimized using an RP-UHPLC separation platform. HRMS-MSMS analysis was conducted on an Orbitrap Velos Elite applying CID. Quantification was performed label-free taking into account ionization properties and physicochemical peptide similarities. Results were analyzed using SIEVE 2.0 (Thermo Fisher Scientific) and SIMCA (Umetrics AG). The developed HRMS platform was applied to an E. Coli expression set with varying productivity and the corresponding downstream process. Selected HCPs were successfully quantified within the fmol range. Analysing HCP networks based on pattern analysis facilitated low level quantification and enhanced validity. This approach is of high relevance for high-throughput screening experiments during upstream development, e.g. for titer determination, dynamic HCP network analysis or product characterization. Considering the downstream purification process, physicochemical clustering of identified HCPs is of relevance to adjust buffer conditions accordingly. However, the technology provides an innovative approach for label-free MS based quantification relying on statistical pattern analysis and comparison. Absolute quantification based on physicochemical properties and peptide similarity score provides a technological approach without the need of sophisticated sample preparation strategies and is therefore proven to be straightforward, sensitive and highly reproducible in terms of product characterization.

Keywords: process analytical technology, mass spectrometry, process characterization, MVDA, pattern recognition

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Authors: Kasra Afsahi, Maryam Soheilifar

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COVID-19 has been associated with stroke and neurological complications. The patient was a 59-year- old male who presented with sudden left hemiparesis and diplopia due to cavernous sinus thrombosis (CST) on 28/03/2020. The COVID-19 test was positive. Multislice CT (MSCT) showed ischemic infarction. He underwent surgical sinectomy 9 days after admission. Physiotherapy began for him in August 2020. Our game-based virtual reality (VR) technology developed for stroke patients was based on upper extremity exercises and function for stroke. After 6 weeks of VR therapy plus conventional physiotherapy exercises (18 sessions, three times per week, 60 minutes each session), there were significant improvements in Brunnstrom Motor Recovery Stage (from “4” to “5”), Fugl-Meyer Scale score of upper extremity section (from 49 to 54), and Modified Barthel Index (from15 to 18). There were no adverse effects. This case with stroke post-COVID-19 due to the CST showed the usefulness of VR therapy used as an adjunct to conventional physiotherapy in improving affected upper extremity.

Keywords: COVID-19, stroke, virtual reality, rehabilitation

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Authors: Zabihullah Mahdi, Khwaja Naweed Seddiqi, Shigeo Honma

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Through many types of research and practical studies, it has been identified that the average oil recovery factor of a petroleum reservoir is about 30 to 35 %. This study is focused on enhanced oil recovery by laboratory experiment and graphical investigation based on Buckley-Leverett theory. Horizontal oil displacement by water, in a petroleum reservoir is analyzed under the Buckley-Leverett frontal displacement theory. The extraction and prerequisite of this theory are based and pursued focusing on the key factors that control displacement. The theory is executable to the waterflooding method, which is generally employed in petroleum engineering reservoirs to sustain oil production recovery, and the techniques for evaluating the average water saturation behind the water front and the oil recovery factors in the reservoirs are presented. In this paper, the Buckley-Leverett theory handled to an experimental model and the amount of recoverable oil are investigated to be over 35%. The irreducible water saturation, viz. connate water saturation, in the reservoir is also a significant inspiration for the recovery.

Keywords: Buckley-Leverett theory, waterflooding technique, petroleum engineering, immiscible displacement

Procedia PDF Downloads 236

Authors: Thuy Phuong Nhat Tran, Ashutosh Thakur, Toshiaki Taniike

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Recently, covalently linked graphene oxide frameworks (GOFs) have attracted considerable attention in gas absorbance and water purification as well-defined microporous materials. In spite of their potential advantages such as a controllable pore dimension, adjustable hydrophobicity, and structural stability, these materials have been scarcely employed in heterogeneous catalysis. Here we demonstrate a novel and facile method to synthesize Pd nanoparticles (NPs) confined in a GOF (Pd@GOF). The GOF with uniform interlayer space was obtained by the intercalation of diboronic acid between graphene oxide layers. It was found that Pd NPs were generated inside the graphitic gallery spaces of the GOF, and thus, formed Pd NPs were well-dispersed with a narrow particle size distribution. The synthesized Pd@GOF emerged as an efficient nanocatalyst based on its superior performance (product yield and recyclability) toward Suzuki-Miyaura cross-coupling reaction in both polar and apolar solvents, which has been hardly observed for previously reported graphene-based Pd nanocatalysts. Furthermore, the rational comparison of the catalytic performance between two kinds of Pd@GOF (Pd NPs encapsulated in a diboronic ester-intercalated GOF and in a monoboronic ester-intercalated GOF) firmly confirmed the essential role of a rigid framework design in the stabilization of Pd NPs. Based on these results, the covalently assembled GOF was proposed as a promising scaffold for hosting noble metal NPs to construct desired metal@GOF nanocatalysts with improved activity and durability.

Keywords: graphene oxide framework, palladium nanocatalyst, pore confinement, Suzuki-Miyaura cross-coupling reaction

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Authors: Jiangbo Li, Wenqian Huang

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Early detection of fungal infection in citrus fruit is one of the major problems in the postharvest commercialization process. The automatic and nondestructive detection of infected fruits is still a challenge for the citrus industry. At present, the visual inspection of rotten citrus fruits is commonly performed by workers through the ultraviolet induction fluorescence technology or manual sorting in citrus packinghouses to remove fruit subject with fungal infection. However, the former entails a number of problems because exposing people to this kind of lighting is potentially hazardous to human health, and the latter is very inefficient. Orange is used as a research object. This study would focus on this problem and proposed an effective method based on Vis-NIR hyperspectral imaging in the wavelength range of 400-1000 nm with a spectroscopic resolution of 2.8 nm. In this work, three normalization approaches are applied prior to analysis to reduce the effect of sample curvature on spectral profiles, and it is found that mean normalization was the most effective pretreatment for decreasing spectral variability due to curvature. Then, principal component analysis (PCA) was applied to a dataset composing of average spectra from decayed and normal tissue to reduce the dimensionality of data and observe the ability of Vis-NIR hyper-spectra to discriminate data from two classes. In this case, it was observed that normal and decayed spectra were separable along the resultant first principal component (PC1) axis. Subsequently, five wavelengths (band) centered at 577, 702, 751, 808, and 923 nm were selected as the characteristic wavelengths by analyzing the loadings of PC1. A multispectral combination image was generated based on five selected characteristic wavelength images. Based on the obtained multispectral combination image, the intensity slicing pseudocolor image processing method is used to generate a 2-D visual classification image that would enhance the contrast between normal and decayed tissue. Finally, an image segmentation algorithm for detection of decayed fruit was developed based on the pseudocolor image coupled with a simple thresholding method. For the investigated 238 independent set samples including infected fruits infected by Penicillium digitatum and normal fruits, the total success rate is 100% and 97.5%, respectively, and, the proposed algorithm also used to identify the orange infected by penicillium italicum with a 100% identification accuracy, indicating that the proposed multispectral algorithm here is an effective method and it is potential to be applied in citrus industry.

Keywords: citrus fruit, early rotten, fungal infection, hyperspectral imaging

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Authors: Lei Zhang, Tingting Xu, Jun He, Zhenyu Yan

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Email marketing is one of the most important segments of online marketing. It has been proved to be the most effective way to acquire and retain customers. The email content is vital to customers. Different customers may have different familiarity with a product, so a successful marketing strategy must personalize email content based on individual customers’ product affinity. In this study, we build our personalized email marketing strategy with three types of emails: nurture, promotion, and conversion. Each type of email has a different influence on customers. We investigate this difference by analyzing customers’ open rates, click rates and opt-out rates. Feature importance from response models is also analyzed. The goal of the marketing strategy is to improve the click rate on conversion-type emails. To build the personalized strategy, we formulate the problem as a reinforcement learning problem and adopt a Q-learning algorithm with variations. The simulation results show that our model-based strategy outperforms the current marketer’s strategy.

Keywords: email marketing, email content, reinforcement learning, machine learning, Q-learning

Procedia PDF Downloads 179

Authors: Sameerah A. Al-Hariri Al-Zahrani

Abstract:

The current study aims at getting acquainted with the impact of the use of some multiple intelligence-based teaching strategies on developing moral intelligence and inferential jurisprudential thinking among secondary school female students. The study has endeavored to answer the following questions: What is the impact of the use of some multiple intelligence-based teaching strategies on developing inferential jurisprudential thinking and moral intelligence among first-year secondary school female students? In the frame of this main research question, the study seeks to answer the following sub-questions: (i) What are the inferential jurisprudential thinking skills among first-year secondary school female students? (ii) What are the components of moral intelligence among first year secondary school female students? (iii) What is the impact of the use of some multiple intelligence‐based teaching strategies (such as the strategies of analyzing values, modeling, Socratic discussion, collaborative learning, peer collaboration, collective stories, building emotional moments, role play, one-minute observation) on moral intelligence among first-year secondary school female students? (iv) What is the impact of the use of some multiple intelligence‐based teaching strategies (such as the strategies of analyzing values, modeling, Socratic discussion, collaborative learning, peer collaboration, collective stories, building emotional moments, role play, one-minute observation) on developing the capacity for inferential jurisprudential thinking of juristic rules among first-year secondary school female students? The study has used the descriptive-analytical methodology in surveying, analyzing, and reviewing the literature on previous studies in order to benefit from them in building the tools of the study and the materials of experimental treatment. The study has also used the experimental method to study the impact of the independent variable (multiple intelligence strategies) on the two dependent variables (moral intelligence and inferential jurisprudential thinking) in first-year secondary school female students’ learning. The sample of the study is made up of 70 female students that have been divided into two groups: an experimental group consisting of 35 students who have been taught through multiple intelligence strategies, and a control group consisting of the other 35 students who have been taught normally. The two tools of the study (inferential jurisprudential thinking test and moral intelligence scale) have been implemented on the two groups as a pre-test. The female researcher taught the experimental group and implemented the two tools of the study. After the experiment, which lasted eight weeks, was over, the study showed the following results: (i) The existence of significant statistical differences (0.05) between the mean average of the control group and that of the experimental group in the inferential jurisprudential thinking test (recognition of the evidence of jurisprudential rule, recognition of the motive for the jurisprudential rule, jurisprudential inferencing, analogical jurisprudence) in favor of the experimental group. (ii) The existence of significant statistical differences (0.05) between the mean average of the control group and that of the experimental group in the components of the moral intelligence scale (sympathy, conscience, moral wisdom, tolerance, justice, respect) in favor of the experimental group. The study has, thus, demonstrated the impact of the use of some multiple intelligence-based teaching strategies on developing moral intelligence and inferential jurisprudential thinking.

Keywords: moral intelligence, teaching, inferential jurisprudential thinking, secondary school

Procedia PDF Downloads 148

Authors: Md. Zahirul Islam, Chad A. Ulven

Abstract:

Fiber-reinforced polymer matrix composites have a wide range of applications in the sectors of automotive, aerospace, sports utilities, among others, due to their high specific strength, stiffness as well as reduced weight. In addition to those favorable properties, composites composed of natural fibers and bio-based resins (i.e., biocomposites) have eco-friendliness and biodegradability. However, the applications of biocomposites are limited due to the lack of knowledge about their long-term reliability under fluctuating loads. In order to explore the long-term reliability of flax fiber reinforced composites under fluctuating loads through high cycle fatigue strength (HCFS), fatigue test were conducted on unidirectional flax fiber reinforced thermoset composites at different percentage loads of ultimate tensile strength (UTS) with a loading frequency of 5 Hz. Change of temperature of the sample during cyclic loading was captured using an IR camera. Initially, the temperature increased rapidly, but after a certain time, it stabilized. A mathematical model was developed to predict the fatigue life from the data of stabilized temperature. Stabilized temperature and dissipated energy per cycle were compared with applied stress. Both showed bilinear behavior and the intersection of those curves were used to determine HCFS. HCFS for unidirectional flax fiber reinforced composites is around 45% of UTS for a loading frequency of 5Hz. Unlike fatigue life, stabilized temperature and dissipated energy-based models are convenient to define HCFS as they have little variation from sample to sample.

Keywords: energy method, fatigue, flax fiber reinforced composite, HCFS, thermographic approach

Procedia PDF Downloads 96

Authors: Omoruyi Gold Idemudia, Alexander P. Sadimenko

Abstract:

The synthesis of N-heterocycles with novel properties, having broad spectrum biological activities that may become alternative medicinal drugs, have been attracting a lot of research attention due to the emergence of medicinal drug’s limitations such as disease resistance and their toxicity effects among others. Acylpyrazolones have been employed as pharmaceuticals as well as analytical reagent and their application as coordination complexes with transition metal ions have been well established. By way of a condensation reaction with amines acylpyrazolone ketones form a more chelating and superior group of compounds known as azomethines. 4-propyl-3-methyl-1-phenyl-2-pyrazolin-5-one was reacted with phenylhydrazine to get a new phenylhydrazone which was further reacted with aqueous solutions of palladium and platinum salts, in an effort towards the discovery of transition metal based synthetic drugs. The compounds were characterized by means of analytical, spectroscopic, thermogravimetric analysis TGA, as well as x-ray crystallography. 4-propyl-3-methyl-1-phenyl-2-pyrazolin-5-one phenylhydrazone crystallizes in a triclinic crystal system with a P-1 (No. 2) space group based on x-ray crystallography. The bidentate ON ligand formed a square planar geometry on coordinating with metal ions based on FTIR, electronic and NMR spectra as well as magnetic moments. Reported compounds showed antibacterial activities against the nominated bacterial isolates using the disc diffusion technique at 20 mg/ml in triplicates. The metal complexes exhibited a better antibacterial activity with platinum complex having an MIC value of 0.63 mg/ml. Similarly, ligand and complexes also showed antioxidant scavenging properties against 2, 2-diphenyl-1-picrylhydrazyl DPPH radical at 0.5mg/ml relative to ascorbic acid (standard drug).

Keywords: acylpyrazolone, antibacterial studies, metal complexes, phenylhydrazone, spectroscopy

Procedia PDF Downloads 239

Authors: M. Richichi

Abstract:

Evidencing the learning and developmental needs of students in specific educational institutions is central to determining the type of whole school pedagogical shift required. Initiating this transition by designing and implementing STEAM (Science, technology, engineering, art, and mathematics) project-based learning opportunities, in collaboration with industry, exposes teachers to new pedagogical and assessment practices. This experience instills confidence and a renewed sense of energy, which contributes to greater efficacy. Championing teachers in such learning environments leads to “bleeding” of inventive pedagogical understanding and skills as well as motivation. This contributes positively to collective teacher efficacy and the transition towards more cross-disciplinary initiatives and opportunities, and hence an innovative pedagogical shift. Evidence of skill and knowledge development in students, combined with greater confidence, work ethic and interest in STEAM areas, are further indicators of the success of the transitioning process.

Keywords: efficacy, pedagogy, transition, STEAM

Procedia PDF Downloads 115

Authors: Debabrata Adhikari, Mikhail Matveev, Louise Brown, Andy Long, Jan Kočí

Abstract:

A good understanding of mesoscale permeability of complex architectures in fibrous porous preforms is of particular interest in order to achieve efficient and cost-effective resin impregnation of liquid composite molding (LCM). Fabrics used in structural reinforcements are typically woven or stitched. However, 3D fabric reinforcement is of particular interest because of the versatility in the weaving pattern with the binder yarn and in-plain yarn arrangements to manufacture thick composite parts, overcome the limitation in delamination, improve toughness etc. To predict the permeability based on the available pore spaces between the inter yarn spaces, unit cell-based computational fluid dynamics models have been using the Stokes Darcy model. Typically, the preform consists of an arrangement of yarns with spacing in the order of mm, wherein each yarn consists of thousands of filaments with spacing in the order of μm. The fluid flow during infusion exchanges the mass between the intra and inter yarn channels, meaning there is no dead-end of flow between the mesopore in the inter yarn space and the micropore in the yarn. Several studies have employed the Brinkman equation to take into account the flow through dual-scale porosity reinforcement to estimate their permeability. Furthermore, to reduce the computational effort of dual scale flow, scale separation criteria based on the ratio between yarn permeability to the yarn spacing was also proposed to quantify the dual scale and negligible micro-scale flow regime for the prediction of mesoscale permeability. In the present work, the key parameter to identify the influence of intra yarn permeability on the mesoscale permeability has been investigated with the systematic study of weft and warp yarn spacing on the plane weave as well as the position of binder yarn and number of in-plane yarn layers on 3D weave fabric. The permeability tensor has been estimated using an OpenFOAM-based model for the various weave pattern with idealized geometry of yarn implemented using open-source software TexGen. Additionally, scale separation criterion has been established based on the various configuration of yarn permeability for the 3D fabric with both the isotropic and anisotropic yarn from Gebart’s model. It was observed that the variation of mesoscale permeability Kxx within 30% when the isotropic porous yarn is considered for a 3D fabric with binder yarn. Furthermore, the permeability model developed in this study will be used for multi-objective optimizations of the preform mesoscale geometry in terms of yarn spacing, binder pattern, and a number of layers with an aim to obtain improved permeability and reduced void content during the LCM process.

Keywords: permeability, 3D fabric, dual-scale flow, liquid composite molding

Procedia PDF Downloads 83