Search results for: fault tree analysis (FTA) method

Authors: M. S. Gaafar, S. Y. Marzouk

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Sodium borosilicate glasses doped with different content of NdF3 mol % have been prepared by rapid quenching method. Ultrasonic velocities (both longitudinal and shear) measurements have been carried out at room temperature and at ultrasonic frequency of 4 MHz. Elastic moduli, Debye temperature, softening temperature and Poisson's ratio have been obtained as a function of NdF3 modifier content. Results showed that the elastic moduli, Debye temperature, softening temperature and Poisson's ratio have very slight change with the change of NdF3 mol % content. Based on FTIR spectroscopy and theoretical (Bond compression) model, quantitative analysis has been carried out in order to obtain more information about the structure of these glasses. The study indicated that the structure of these glasses is mainly composed of SiO4 units with four bridging oxygens (Q4), and with three bridging and one nonbridging oxygens (Q3).

Keywords: borosilicate glasses, ultrasonic velocity, elastic moduli, FTIR spectroscopy, bond compression model

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Authors: Arash Ahmadi, Amirreza Kavousizadeh, Sanaz Heidarzadeh

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Stage-discharge curve is one of the conventional methods for continuous river flow measurement. In this paper, an innovative approach is proposed for predicting the stage-discharge relationship using the application of isovel contours. Using the proposed method, it is possible to estimate the stage-discharge curve in the whole section with only using discharge information from just one arbitrary water level. For this purpose, multivariate relationships are used to determine the mean velocity in a cross-section. The unknown exponents of the proposed relationship have been obtained by using the second version of the Strength Pareto Evolutionary Algorithm (SPEA2), and the appropriate equation was selected by applying the TOPSIS (Technique for Order Preferences by Similarity to an Ideal Solution) approach. Results showed a close agreement between the estimated and observed data in the different cross-sections.

Keywords: rating curves, SPEA2, natural rivers, bed roughness distribution

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Authors: Chui-Hsin Chen, Yu-Ting Chen

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Special concentrically braced frames is one of the seismic load resisting systems, which dissipates seismic energy when bracing members within the frames undergo yielding and buckling while sustaining their axial tension and compression load capacities. Most of the inelastic deformation of a buckling bracing member concentrates in the mid-length region. While experiencing cyclic loading, the region dissipates most of the seismic energy being input into the frame. Such a concentration makes the braces vulnerable to failure modes associated with low-cycle fatigue. In this research, a strategy to improve the cyclic behavior of the conventional steel bracing member is proposed by filling the Hollow Structural Shape (HSS) member with reinforcement. It prevents the local section from concentrating large plastic deformation caused by cyclic loading. The infill helps spread over the plastic hinge region into a wider area hence postpone the initiation of local buckling or even the rupture of the braces. The finite element method is introduced to simulate the complicated bracing member behavior and member-versus-infill interaction under cyclic loading. Fifteen 3-D-element-based models are built by ABAQUS software. The verification of the FEM model is done with unreinforced (UR) HSS bracing members’ cyclic test data and aluminum honeycomb plates’ bending test data. Numerical models include UR and filled HSS bracing members with various compactness ratios based on the specification of AISC-2016 and AISC-1989. The primary variables to be investigated include the relative bending stiffness and the material of the filling reinforcement. The distributions of von Mises stress and equivalent plastic strain (PEEQ) are used as indices to tell the strengths and shortcomings of each model. The result indicates that the change of relative bending stiffness of the infill is much more influential than the change of material in use to increase the energy dissipation capacity. Strengthen the relative bending stiffness of the reinforcement results in additional energy dissipation capacity to the extent of 24% and 46% in model based on AISC-2016 (16-series) and AISC-1989 (89-series), respectively. HSS members with infill show growth in 𝜂Local Buckling, normalized energy cumulated until the happening of local buckling, comparing to UR bracing members. The 89-series infill-reinforced members have more energy dissipation capacity than unreinforced 16-series members by 117% to 166%. The flexural rigidity of infills should be less than 29% and 13% of the member section itself for 16-series and 89-series bracing members accordingly, thereby guaranteeing the spread over of the plastic hinge and the happening of it within the reinforced section. If the parameters are properly configured, the ductility, energy dissipation capacity, and fatigue-life of HSS SCBF bracing members can be improved prominently by the infill-reinforced method.

Keywords: special concentrically braced frames, HSS, cyclic loading, infill reinforcement, finite element analysis, PEEQ

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Authors: B. Shaw, K. Doherty

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The Cultural Communication and Computing Research Institute (C3RI) is a diverse multidisciplinary research institute including art, design, media production, communication studies, computing and engineering. Across these disciplines it can seem like there are enormous differences of research practice and convention, including differing positions on objectivity and subjectivity, certainty and evidence, and different political and ethical parameters. These differences sit within, often unacknowledged, histories, codes, and communication styles of specific disciplines, and it is all these aspects that can make understanding of research practice across disciplines difficult. To explore this, a one day event was orchestrated, testing how a PhD community might communicate and share research in progress in a multi-disciplinary context. Instead of presenting results at a conference, research students were tasked to articulate their method of inquiry. A working party of students from across disciplines had to design a conference call, visual identity and an event framework that would work for students across all disciplines. The process of establishing the shape and identity of the conference was revealing. Even finding a linguistic frame that would meet the expectations of different disciplines for the conference call was challenging. The first abstracts submitted either resorted to reporting findings, or only described method briefly. It took several weeks of supported intervention for research students to get ‘inside’ their method and to understand their research practice as a process rich with philosophical and practical decisions and implications. In response to the abstracts the conference committee generated key methodological categories for conference sessions, including sampling, capturing ‘experience’, ‘making models’, researcher identities, and ‘constructing data’. Each session involved presentations by visual artists, communications students and computing researchers with inter-disciplinary dialogue, facilitated by alumni Chairs. The apparently simple focus on method illuminated research process as a site of creativity, innovation and discovery, and also built epistemological awareness, drawing attention to what is being researched and how it can be known. It was surprisingly difficult to limit students to discussing method, and it was apparent that the vocabulary available for method is sometimes limited. However, by focusing on method rather than results, the genuine process of research, rather than one constructed for approval, could be captured. In unlocking the twists and turns of planning and implementing research, and the impact of circumstance and contingency, students had to reflect frankly on successes and failures. This level of self – and public- critique emphasised the degree of critical thinking and rigour required in executing research and demonstrated that honest reportage of research, faults and all, is good valid research. The process also revealed the degree that disciplines can learn from each other- the computing students gained insights from the sensitive social contextualizing generated by communications and art and design students, and art and design students gained understanding from the greater ‘distance’ and emphasis on application that computing students applied to their subjects. Finding the means to develop dialogue across disciplines makes researchers better equipped to devise and tackle research problems across disciplines, potentially laying the ground for more effective collaboration.

Keywords: interdisciplinary, method, research student, training

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Authors: Dmitry V. Fomichev, Vladimir V. Solonin

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This paper presents the findings from a numerical simulation of the flow in 37-rod fuel assembly models spaced by a double-wire trapezoidal wrapping as applied to the BREST-OD-300 experimental nuclear reactor. Data on a high static pressure distribution within the models, and equations for determining the fuel bundle flow friction factors have been obtained. Recommendations are provided on using the closing turbulence models available in the ANSYS Fluent. A comparative analysis has been performed against the existing empirical equations for determining the flow friction factors. The calculated and experimental data fit has been shown. An analysis into the experimental data and results of the numerical simulation of the BREST-OD-300 fuel rod assembly hydrodynamic performance are presented.

Keywords: BREST-OD-300, ware-spaces, fuel assembly, computation fluid dynamics

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Authors: Agata Matuszewska, Małgorzata Syczewska

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The movement of the upper limbs contributes significantly to balance control while walking in humans. However, the impact of different arm swing modes on gait stability is yet to be determined. This work intends to establish numerical parameters for assessing the arm swing. Nineteen people, comprising fifteen young, healthy individuals, two middle-aged individuals, and two individuals with dysfunctions, were analyzed using the movement analysis system. Proposed parameters such as ASᵢₐ (reflecting the arm swing amplitude) and Pearson’s correlation coefficient between the right and left upper limbs can be used to classify the type of movement task each participant performs. The results indicate that the ASᵢₐ parameter could potentially detect any abnormalities in upper limb functions, which may be due to musculoskeletal disorders or other malfunctions.

Keywords: arm swing, human balance, interlimb coordination, motion analysis system

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Authors: Ngozi Claribelle Nwogu, Mohammed Nasir Kajama, Oyoh Kechinyere, Edward Gobina

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Atmospheric carbon dioxide emissions are considered as the greatest environmental challenge the world is facing today. The challenges to control the emissions include the recovery of CO2 from flue gas. This concern has been improved due to recent advances in materials process engineering resulting in the development of inorganic gas separation membranes with excellent thermal and mechanical stability required for most gas separations. This paper therefore evaluates the performance of a highly selective inorganic membrane for CO2 recovery applications. Analysis of results obtained is in agreement with experimental literature data. Further results show the prediction performance of the membranes for gas separation and the future direction of research. The materials selection and the membrane preparation techniques are discussed. Method of improving the interface defects in the membrane and its effect on the separation performance has also been reviewed and in addition advances to totally exploit the potential usage of this innovative membrane.

Keywords: carbon dioxide, gas separation, inorganic ceramic membrane, permselectivity

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Authors: Mohit Batra, Noel Sarkar, Jayeeta Mitra

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In this study silica nanoparticles were synthesized using different methods and different silica sources namely Tetraethyl ortho silicate (TEOS), Sodium Silicate, Rice husk while chitosan nanoparticles were prepared with ionic gelation method using Sodium tripolyphosphate (TPP). Size and texture of silica nanoparticles were studied using field emission scanning electron microscopy (FESEM) and transmission electron microscopy (TEM) along with the effect of change in concentration of various reagents in different synthesis processes. Size and dispersion of Silica nanoparticles prepared from TEOS using stobber’s method were found better than other methods while nanoparticles prepared using rice husk were cheaper than other ones. Catalyst found to play a very significant role in controlling the size of nanoparticles in all methods.

Keywords: silica nanoparticles, gelatin, bio-nanocomposites, SEM, TEM, chitosan

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Francky Fouedjio

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Multivariate geostatistical data have become omnipresent in the geosciences and pose substantial analysis challenges. One of them is the grouping of data locations into spatially contiguous clusters so that data locations within the same cluster are more similar while clusters are different from each other, in some sense. Spatially contiguous clusters can significantly improve the interpretation that turns the resulting clusters into meaningful geographical subregions. In this paper, we develop an agglomerative hierarchical clustering approach that takes into account the spatial dependency between observations. It relies on a dissimilarity matrix built from a non-parametric kernel estimator of the spatial dependence structure of data. It integrates existing methods to find the optimal cluster number and to evaluate the contribution of variables to the clustering. The capability of the proposed approach to provide spatially compact, connected and meaningful clusters is assessed using bivariate synthetic dataset and multivariate geochemical dataset. The proposed clustering method gives satisfactory results compared to other similar geostatistical clustering methods.

Keywords: clustering, geostatistics, multivariate data, non-parametric

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Authors: Siriporn Meenanan

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The objective of this study is to investigate the attitude of Thai students towards the Thai series "Hormones the Series Season 2". This study was conducted in the quantitative research, and the questionnaires were used to collect data from 400 people of the sample group. Descriptive statistics were used in data analysis. The findings reveal that most participants have positive comments regarding the series. They strongly agreed that the series reflects on the way of life and problems of teenagers in Thailand. Hence, the participants believe that if adults have a chance to watch the series, they will have the better understanding of the teenagers. In addition, the participants also agreed that the contents of the play are appropriate and satisfiable as the contents of “Hormones the Series Season 2” will raise awareness among the teens and use it as a guide to prevent problems that might happen during their teenage life.

Keywords: content analysis, attitude, Thai series, hormones the Series

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Authors: Qian Yi Ooi

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At present, airfoil parameters are still designed and optimized according to the scale of conventional aircraft, and there are still some slight deviations in terms of scale differences. However, insufficient parameters or poor surface mesh quality is likely to occur if these small deviations are embedded in a future civil aircraft with a size that is quite different from conventional aircraft, such as a blended-wing-body (BWB) aircraft with future potential, resulting in large deviations in geometric similarity in computational fluid dynamics (CFD) simulations. To avoid this situation, the study on the CFD calculation on the geometric similarity of airfoil parameters and the quality of the surface mesh is conducted to obtain the ability of different parameterization methods applied on different airfoil scales. The research objects are three airfoil scales, including the wing root and wingtip of conventional civil aircraft and the wing root of the giant hybrid wing, used by three parameterization methods to compare the calculation differences between different sizes of airfoils. In this study, the constants including NACA 0012, a Reynolds number of 10 million, an angle of attack of zero, a C-grid for meshing, and the k-epsilon (k-ε) turbulence model are used. The experimental variables include three airfoil parameterization methods: point cloud method, B-spline curve method, and class function/shape function transformation (CST) method. The airfoil dimensions are set to 3.98 meters, 17.67 meters, and 48 meters, respectively. In addition, this study also uses different numbers of edge meshing and the same bias factor in the CFD simulation. Studies have shown that with the change of airfoil scales, different parameterization methods, the number of control points, and the meshing number of divisions should be used to improve the accuracy of the aerodynamic performance of the wing. When the airfoil ratio increases, the most basic point cloud parameterization method will require more and larger data to support the accuracy of the airfoil’s aerodynamic performance, which will face the severe test of insufficient computer capacity. On the other hand, when using the B-spline curve method, average number of control points and meshing number of divisions should be set appropriately to obtain higher accuracy; however, the quantitative balance cannot be directly defined, but the decisions should be made repeatedly by adding and subtracting. Lastly, when using the CST method, it is found that limited control points are enough to accurately parameterize the larger-sized wing; a higher degree of accuracy and stability can be obtained by using a lower-performance computer.

Keywords: airfoil, computational fluid dynamics, geometric similarity, surface mesh quality

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Authors: Amira Amamou, Mnaouar Chouchane

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This paper investigates the bifurcation and nonlinear behavior of two degrees of freedom model of a symmetrical balanced rigid rotor supported by two identical journal bearings. The fluid film hydrodynamic reactions are modeled by applying both the short and the long bearing approximation and using half Sommerfeld solution. A numerical integration of equations of the journal centre motion is presented to predict the presence and the size of stable or unstable limit cycles in the neighborhood of the stability critical speed. For their stability margins, a continuation method based on the predictor-corrector mechanism is used. The numerical results of responses show that stability and bifurcation behaviors of periodic motions depend strongly on bearing parameters and its dynamic characteristics.

Keywords: hydrodynamic journal bearing, nonlinear stability, continuation method, bifurcations

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Authors: Rizwana Amin, Afshan Afroze Bhatti

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The study was a quasi-experimental pre-post test design including two groups. Data was collected from 127 students through non-probability random sampling from Bahaudin Zakariya University Multan. The groups were given pre-test using perceived stress scale and information about academic achievement was taken by self-report. After screening, 27 participants didn’t meet the criterion. Remaining 100 participants were divided into two groups (experimental and control). Further, 4 students of experimental group denied taking intervention. Then 46 understudies were separated into three subgroups (16, 15 and 15 in each) for training. The experimental groups were given the stress management training, each of experimental group attended one 3-hour training sessions separately while the control group was only given pre-post assessment. The data were analyzed using ANCOVA method (analysis of covariance) t–test. Results of the study indicate that stress training will lead to increased emotional intelligence and academic achievement of students.

Keywords: stress, stress management, academic achievement, students

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Authors: Mehrdad Abkenari, Mehmet Kunt, Mahdi Nourollahi

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Evaluating the environmental risk factors is a combination of analysis of transportation effects. Various definitions for risk can be found in different scientific sources. Each definition depends on a specific and particular perspective or dimension. The effects of potential risks present along the new proposed routes and existing infrastructures of large transportation projects like railways should be studied under comprehensive engineering frameworks. Despite various definitions provided for ‘risk’, all include a uniform concept. Two obvious aspects, loss and unreliability, have always been pointed in all definitions of this term. But, selection as the third aspect is usually implied and means how one notices it. Currently, conducting engineering studies on the environmental effects of railway projects have become obligatory according to the Environmental Assessment Act in developing countries. Considering the longitudinal nature of these projects and probable passage of railways through various ecosystems, scientific research on the environmental risk of these projects have become of great interest. Although many areas of expertise such as road construction in developing countries have not seriously committed to these studies yet, attention to these subjects in establishment or implementation of different systems have become an inseparable part of this wave of research. The present study used environmental risks identified and existing in previous studies and stations to use in next step. The second step proposes a new hybrid approach of analytical network process (ANP) and DEMATEL in fuzzy conditions for assessment of determined risks. Since evaluation of identified risks was not an easy touch, mesh structure was an appropriate approach for analyzing complex systems which were accordingly employed for problem description and modeling. Researchers faced the shortage of real space data and also due to the ambiguity of experts’ opinions and judgments, they were declared in language variables instead of numerical ones. Since fuzzy logic is appropriate for ambiguity and uncertainty, formulation of experts’ opinions in the form of fuzzy numbers seemed an appropriate approach. Fuzzy DEMATEL method was used to extract the relations between major and minor risk factors. Considering the internal relations of risk major factors and its sub-factors in the analysis of fuzzy network, the weight of risk’s main factors and sub-factors were determined. In general, findings of the present study, in which effective railway environmental risk indicators were theoretically identified and rated through the first usage of combined model of DEMATEL and fuzzy network analysis, indicate that environmental risks can be evaluated more accurately and also employed in railway projects.

Keywords: DEMATEL, ANP, fuzzy, risk

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Authors: Mahshid Davoodpoor, Zahra Shamohammadi Ghahsareh, Saeid Razfar, Alaleh Dabbaghi

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Nowadays, air pollution has become a topic of great concern all over the world. One of the main sources of air pollution is automobile exhaust gas, which introduces a large number of toxic gases, including CO, unburned hydrocarbons (HCs), NOx, and non-methane hydrocarbons (NMHCs), into the air. The application of three-way catalysts (TWCs) is still the most effective strategy to mitigate the emission of these pollutants. Due to the stringent environmental regulations which continuously become stricter, studies on the TWCs are ongoing despite several years of research and development. This arises from the washcoat complexity and the several numbers of parameters involved in the redox reactions. The main objectives of these studies are the optimization of washcoat formulation and the investigation of different coating modes. Perovskite (ABO₃), as a promising class of materials, has unique features that make it versatile to use as an alternative to commonly mixed oxides in washcoats. High catalytic activity for oxidation reactions and its relatively high oxygen storage capacity are important properties of perovskites in catalytic applications. Herein, La₀.₈Ba₀.₂FeO₃ perovskite material was synthesized using the co-precipitation method and characterized by XRD, ICP, and BET analysis. The effect of synthesis conditions, including B site metal (Fe and Co), metal precursor concentration, and dopant (Ba), were examined on the phase purity of the products. The selected perovskite sample was used as one of the components in the TWC formulation to evaluate its catalytic performance through Light-off, oxygen storage capacity, and emission analysis. Results showed a remarkable increment in oxygen storage capacity and also revealed that T50 and emission of CO, HC, and NOx reduced in the presence of perovskite structure which approves the enhancement of catalytic performance for the new washcoat formulation. This study shows the brilliant future of advanced oxide structures in the TWCs.

Keywords: Perovskite, three-way catalyst, PGMs, PGMs reduction

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Authors: Nagwa Abouserie Soliman

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The Victorian era, which started with the reign of Queen Victoria from June 1837 to January 1901, could be considered as one of the most significant eras that had a crucial impact which formed contemporary British life despite the fact that with the rise of the British empire many negative aspects surfaced, namelysocial inequalities such as class differences, child labor, population increase and poverty due to the industrial revolution. Charles Dickens was one of the most prominent writers of the Victorian era who perceived the hypocrisy of the Victorian mores. The appropriate researchstyle that was chosen for this literary analysis is a qualitative research method in which the researcher used the conceptual approach to analyse theDickensian characterisation andwriting style through diction, narrative voice, and images. The aim of this paper is to argue that Charles Dickens inGreat Expectations (1861) was highly satirical of the Victorian mores, as he uses a lot of sharp irony-to satirize various Victorian traditions such as class divisions, the justice system, the poor working class, and the upper-class snobbery that he thought are inhumane and unjust.

Keywords: victorian, child labour, poverty, class division, snobbery

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Authors: Ali Asheibi

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The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

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Authors: Raif Parlakkaya, Ahmet Diken, Erkan Kara

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This paper examines the relationship between corporate governance rating and stock prices of 26 Turkish firms listed in Turkish stock exchange (Borsa Istanbul) by using panel data analysis over five-year period. The paper also investigates the stock performance of firms with governance rating with regards to the market portfolio (i.e. BIST 100 Index) both prior and after governance scoring began. The empirical results show that there is no relation between corporate governance rating and stock prices when using panel data for annual variation in both rating score and stock prices. Further analysis indicates surprising results that while the selected firms outperform the market significantly prior to rating, the same performance does not continue afterwards.

Keywords: corporate governance, stock price, performance, panel data analysis

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Authors: Ha Hai Duong, Amnon Levy Livermore, Kankesu Jayanthakumaran, Oleg Yerokhin

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The issues of economic development, the environment and human health have been investigated since 1990s. Previous researchers have found different empirical evidences of the relationship between income and environmental pollution, health as determinant of economic growth, and the effects of income and environmental pollution on health in various regions of the world. This paper concentrates on integrative relationship analysis of GDP, carbon dioxide emissions, and health services and population health in context of Vietnam. We applied the dynamic generalized method of moments (GMM) estimation on datasets of Vietnam’s sixty-three provinces for the years 2000-2010. Our results show the significant positive effect of GDP on emissions and the dependence of population health on emissions and health services. We find the significant relationship between population health and GDP. Additionally, health services are significantly affected by population health and GDP. Finally, the population size too is other important determinant of both emissions and GDP.

Keywords: economic development, emissions, environmental pollution, health

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Authors: Indira Kothalanka

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For individuals born with a cleft palate (CP), there is no separation between the nasal cavity and the oral cavity, due to which they cannot build up enough air pressure in the mouth for speech. Therefore, it is common for them to have speech problems. Common cleft type speech errors include abnormal articulation (compensatory or obligatory) and abnormal resonance (hyper, hypo and mixed nasality). These are generally resolved after palate repair. However, in some individuals, articulation problems do persist even after the palate repair. Such individuals develop variant articulations in an attempt to compensate for the inability to produce the target phonemes. A spectrographic analysis is used to investigate the compensatory articulatory behaviours of pressure consonants in the speech of 10 Telugu speaking individuals aged between 7-17 years with a history of cleft palate. Telugu is a Dravidian language which is spoken in Andhra Pradesh and Telangana states in India. It is a language with the third largest number of native speakers in India and the most spoken Dravidian language. The speech of the informants is analysed using single word list, sentences, passage and conversation. Spectrographic analysis is carried out using PRAAT, speech analysis software. The place and manner of articulation of consonant sounds is studied through spectrograms with the help of various acoustic cues. The types of compensatory articulation identified are glottal stops, palatal stops, uvular, velar stops and nasal fricatives which are non-native in Telugu.

Keywords: cleft palate, compensatory articulation, spectrographic analysis, PRAAT

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Authors: Parisa Ahmadi Oliaei, Seyed Abolhassan Naeini

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The knowledge of soil–reinforcement interaction parameters is particularly important in the design of reinforced soil structures. The pull-out test is one of the most widely used tests in this regard. The results of tensile tests may be very sensitive to boundary conditions, and more research is needed for a better understanding of the Pull-out response of reinforcement, so numerical analysis using the finite element method can be a useful tool for the understanding of the Pull-out response of soil-geogrid interaction. The main objective of the present study is to compare the numerical and experimental results of Pull- out a test on geogrid-reinforced sandy soils interactions. Plaxis 2D finite element software is used for simulation. In the present study, the pull-out test modeling has been done on sandy soil. The effect of geogrid hardness was also investigated by considering two different types of geogrids. The numerical results curve had a good agreement with the pull-out laboratory results.

Keywords: plaxis, pull-out test, sand, soil- geogrid interaction

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Authors: Wahiba Mohguen, Raïs El’hadi Bekka

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This paper presents a denoising method called EMD-Custom that was based on Empirical Mode Decomposition (EMD) and the modified Customized Thresholding Function (Custom) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs got threshold by applying the presented thresholding function to suppress noise and to improve the signal to noise ratio (SNR). The method was tested on simulated data and real ECG signal, and the results were compared to the EMD-Based signal denoising methods using the soft and hard thresholding. The results showed the superior performance of the proposed EMD-Custom denoising over the traditional approach. The performances were evaluated in terms of SNR in dB, and Mean Square Error (MSE).

Keywords: customized thresholding, ECG signal, EMD, hard thresholding, soft-thresholding

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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A method and system for neuropsychological performance test, comprising a mobile terminal, used to interact with a cloud server which stores user information and is logged into by the user through the terminal device; the user information is directly accessed through the terminal device and is processed by artificial neural network, and the user information comprises user facial emotions information, performance test answers information and user chronometrics. This assessment is used to evaluate the cognitive performance and emotional response of the subject to a series of dichotomous questions describing various situations of daily life and challenging the users' knowledge, values, ethics, and principles. In industrial applications, the timing of this assessment will depend on the users' need to obtain a service from a provider, such as opening a bank account, getting a mortgage or an insurance policy, authenticating clearance at work, or securing online payments.

Keywords: artificial intelligence, neurofinance, neuropsychology, risk management

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Authors: Viloria Marin Hermes, Paredes Santiago Maritza, Viloria Paredes Jonathan

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The aim of this study is to assess the prevalence of Burnout syndrome in a sample of 600 professors at the University of Guayaquil (Ecuador) using the Maslach Burnout Inventory (M.B.I.). In addition, assessment was made of the effects on health from professional burnout using the General Health Questionnaire (G.H.Q.-28), and the influence of Emotional Intelligence on prevention of its symptoms using the Spanish version of the Trait Meta-Mood Scale (T.M.M.S.-24). After confirmation of the underlying factor structure, the three measurement tools showed high levels of internal consistency, and specific cut-off points were proposed for the group of Latin American academics in the M.B.I. Statistical analysis showed the syndrome is present extensively, particularly on medium levels, with notably low scores given for Professional Self-Esteem. The application of Canonical Correspondence Analysis revealed that low levels of self-esteem are related to depression, with a lack of personal resources related to anxiety and insomnia, whereas the ability to perceive and control emotions and feelings improves perceptions of professional effectiveness and performance.

Keywords: burnout, academics, emotional intelligence, general health, canonical correspondence analysis

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Authors: Annemari Munk Svendsen, Jesper Tinggaard Svendsen

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The purpose of this study was to investigate different discourses about the body, movement and the main progression in and aim of Physical Education (PE) that are immersed within Physical Education Teacher Education (PETE) textbooks. The study was based on an examination of Danish PETE course documents listing 296 educational texts prescribed by PETE teachers for PETE programs in Denmark. It presents a more specific analysis of the 20 most used textbooks in Danish PETE. The study found three different discourses termed: (1) Developing the potential for sport, (2) Basis for creative sensing and (3) Being part of a cultural ballast. These discourses represent different ways of conceptualising and appraising PE as a school subject. The results also suggest that PETE textbooks are deeply involved in the (re)construction, struggling and ‘working’ of classical discourses in PE. Furthermore, that PETE textbooks comprise powerful documents that through their recurrent use of high modality are tending to be unequivocal in their suggestions for PE practices. On the basis of these findings, the presentation suggests that PETE teachers may use textbook analysis in the educational program as a tool for enhancing critical reflections upon central ideological dilemmas in PE.

Keywords: critical discourse analysis, critical reflection, physical education teacher education, textbooks

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Authors: E. Pretorius, A. M. Viljoen, M. van der Bank

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Introduction: The phytochemistry of Agathosma crenulata and A. betulina has been studied extensively, while their molecular analysis through DNA barcoding remains virtually unexplored. This technique can confirm the identity of plant species included in a herbal product, thereby ensuring the efficacy of the herbal product and the accuracy of its label. Materials and methods: Authentic Agathosma reference material of A. betulina (n=16) and A. crenulata (n=10) were obtained. Thirteen commercial products were purchased from various health shops around Johannesburg, South Africa, using the search term “Agathosma” or “Buchu.” The plastid regions matK and ycf1 were used to barcode the Buchu products, and BRONX analysis confirmed the taxonomic identity of the samples. UPLC-MS analyses were also performed. Results: Only (30/60) 60% of the traded samples tested from 13 suppliers contained A. betulina in their herbal products. Similar results were also obtained for the UPLC-MS analysis. Conclusion: In this study, we demonstrate the application of DNA barcoding in combination with phytochemical analysis to authenticate herbal products claiming to contain Agathosma plants as an ingredient in their products. This supports manufacturing efforts to ensure that herbal products that are safe for the consumer.

Keywords: Buchu, substitution, barcoding, BRONX algorithm, matK, ycf1, UPLC-MS

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Authors: Shawna Staud, Mary Kaye Scaramucci

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Objective: Rubber cup polishing has been a traditional method of preventative therapy in dental hygiene treatment. Newer methods such as air polishing have changed the way dental hygiene care is provided, yet this technique has not been embraced by students in the program nor by practitioners in the workforce. Students entering the workforce tend to follow office protocol and are limited in confidence to introduce technologies learned in the curriculum. This project was designed to help students gain confidence in newer skills and encourage private practice settings to adopt newer technologies for patient care. Our program recently introduced air polishing earlier in the program before the rubber cup technique to determine if students would embrace the technology to become leading-edge professionals when they enter the marketplace. Methods: The class of 2022 was taught the traditional method of polishing in the first-year curriculum and air polishing in the second-year curriculum. The class of 2023 will be taught the air polishing method in the first-year curriculum and the traditional method of polishing in the second-year curriculum. Pre- and post-graduation survey data will be collected from both cohorts. Descriptive statistics and pre and post-paired t-tests with alpha set at .05 to compare pre and post-survey results will be used to assess data. Results: This study is currently in progress, with a completion date of October 2023. The class of 2022 completed the pre-graduation survey in the spring of 2022. The post-gradation survey will be sent out in October 2022. The class of 2023 cohort will be surveyed in the spring of 2023 and October 2023. Conclusion: Our hypothesis is students who are taught air polishing first will be more inclined to adopt that skill in private practice, thereby embracing newer technology and improving oral health care.

Keywords: luggage handling system at world’s largest pilgrimage center

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Authors: Mohamed Moussaoui, Mouna Baassi, Soukayna Baammi, Hatim Soufi, Mohammed Salah, Rachid Daoud, Achraf EL Allali, Mohammed Elalaoui Belghiti, Said Belaaouad

Abstract:

The present study aims to investigate the quantitative structure-activity relationship (QSAR) of a series of Thiazole derivatives reported as anticancer agents (hepatocellular carcinoma), using principally the electronic descriptors calculated by the density functional theory (DFT) method and by applying the multiple linear regression method. The developed model showed good statistical parameters (R²= 0.725, R²ₐ𝒹ⱼ= 0.653, MSE = 0.060, R²ₜₑₛₜ= 0.827, Q²𝒸ᵥ = 0.536). The energy of the highest occupied molecular orbital (EHOMO) orbital, electronic energy (TE), shape coefficient (I), number of rotatable bonds (NROT), and index of refraction (n) were revealed to be the main descriptors influencing the anti-cancer activity. Additional Thiazole derivatives were then designed and their activities and pharmacokinetic properties were predicted using the validated QSAR model. These designed molecules underwent evaluation through molecular docking (MD) and molecular dynamic (MD) simulations, with binding affinity calculated using the MMPBSA script according to a 100 ns simulation trajectory. This process aimed to study both their affinity and stability towards Cyclin-Dependent Kinase 2 (CDK2), a target protein for cancer disease treatment. The research concluded by identifying four CDK2 inhibitors - A1, A3, A5, and A6 - displaying satisfactory pharmacokinetic properties. MDs results indicated that the designed compound A5 remained stable in the active center of the CDK2 protein, suggesting its potential as an effective inhibitor for the treatment of hepatocellular carcinoma. The findings of this study could contribute significantly to the development of effective CDK2 inhibitors.

Keywords: QSAR, ADMET, Thiazole, anticancer, molecular docking, molecular dynamic simulations, MMPBSA calculation

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Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

Abstract:

For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

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