Search results for: effect of collaborative learning

Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany

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In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.

Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities

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Authors: Lina Jassim, Robiah Yunus, , Amran Salleh

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Since nano particles have been assessed as thermo stabilizer, rheology enhancer, and ecology safer, nano drilling fluid can be utilized to overcome the complexity of hole cleaning in highly deviated interval of an extended reach wells. The eccentric annular flow is a flow with special considerations; it forms a vital part of drilling fluid flow analysis in an extended reach wells. In this work eccentric, dual phase flow (different types of rock cuttings with different size were blended with nano fluid) through horizontal well (an extended reach well) are simulated with the help of CFD, Fluent package. In horizontal wells flow occurs in an adverse pressure gradient condition, that makes the particle inside it susceptible to reversed flow. Thus the flow has to be analyzed in a three dimensional manner. Moreover the non-Newtonian behavior of the nano fluid makes the problem really challenging in numerical and physical aspects. The primary objective of the work is to establish a relationship between different flow characteristics with the speed of inner wall rotation. The nano fluid flow characteristics include swirl of flow and its effect on wellbore cleaning ability , wall shear stress and its effect on fluid viscosity to suspend and carry the rock cuttings, axial velocity and its effect on transportation of rock cuttings to the wellbore surface, finally pressure drop and its effect on managed of drilling pressure. The importance of eccentricity of the inner cylinder has to be analyzed as a part of it. Practical horizontal well flows contain a good amount of particles (rock cuttings) with moderate axial velocity, which verified nano drilling fluid ability of carrying and transferring cuttings particles in the highly deviated eccentric annular flow is also of utmost importance.

Keywords: Non-Newtonian, dual phase, eccentric annular, CFD

Procedia PDF Downloads 433

Authors: Vladimír Frišták, Martin Pipíška, Juraj Lesný

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Alginate has been evaluated as an efficient pollution control material. In this paper, alginate from maar Pinciná (SR) for removal of Cd2+ ions from aqueous solution was studied. The potential sorbent was characterized by X-Ray Fluorescence Analysis (RFA) analysis, Fourier Transform Infrared Spectral Analysis (FT-IR) and Specific Surface Area (SSA) was also determined. The sorption process was optimized from the point of initial cadmium concentration effect and effect of pH value. The Freundlich and Langmuir models were used to interpret the sorption behaviour of Cd2+ ions, and the results showed that experimental data were well fitted by the Langmuir equation. Alginate maximal sorption capacity (QMAX) for Cd2+ ions calculated from Langmuir isotherm was 34 mg/g. Sorption process was significantly affected by initial pH value in the range from 4.0-7.0. Alginate is a comparable sorbent with other materials for toxic metals removal.

Keywords: alginates, Cd2+, sorption, QMAX

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Authors: Akumeyam Elvis Akum, Njanjo Thecla Anyongo Mukete, Fonkeng George Epah

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Globally, the goal of higher education is to enhance graduate employability skills. Paradoxically, Cameroon’s graduate employability rate is far below the graduation rate. This worrisome situation caused the researcher to hypothesize that the teaching and learning experiences account for this increasing disparity. The study sought to investigate the effect on graduate employability of the teaching of organizational, problem-solving, innovation, and risk management skills on graduate employability. The study adopted a descriptive survey design with a quantitative approach. Data was collected by quantitative techniques from a random sample of 385 graduates using closed-ended structured questionnaire. Generally, findings revealed that entrepreneurship education does not sufficiently enhance graduate employability in the University of Buea. Specifically, the teaching of organizational skills does not significantly enhance their employability, as an average of 55% of graduates indicated that the course did not sufficiently help them develop skills for planning, management of limited resources, collaboration, and the setting of priorities. Also, 60% of the respondents indicated that the teaching of problem-solving skills does not significantly enhance graduate employability at the University of Buea. Contrarily, 57% of the respondents agreed that through their experiences in entrepreneurship education, their innovation skills were improved. The study recommended that a practical approach to teaching should be adopted, with attention to societal needs. A framework to ensure the teaching of entrepreneurship to students at the undergraduate level is recommended, such that those who do not continue with university studies after their Bachelor’s degree would have acquired the needed skills for employability.

Keywords: employability, entrepreneurship education, graduate, innovative skills, organizational skills, problem-solving skills, risk management skills

Procedia PDF Downloads 77

Authors: Pouriya Darabiyan, Hadis Nazari, Kourosh Zarea, Saeed Ghanbari, Zeinab Raiesifar, Morteza Khafaie, Hanna Tuvesson

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Introduction Since the beginning of mobile phone addiction, alexithymia, depression, anxiety and stress have been stated as risk factors for Internet addiction, so this study was conducted with the aim of investigating the relationship between Alexithymia and Mobile phone addiction along with the mediating role of anxiety, stress and depression. Materials and methods In this descriptive-analytical and cross-sectional study in 2022, 412 students School of Nursing & Midwifery of Ahvaz Jundishapur University of Medical Sciences were included in the study using available sampling method. Data collection tools were: Demographic Information Questionnaire, Toronto Alexithymia Scale (TAS-20), Depression, Anxiety, Stress Scale (DASS-21) and Mobile Phone Addiction Index (MPAI). Frequency, Pearson correlation coefficient test and linear regression were used to describe and analyze the data. Also, structural equation models and path analysis method were used to investigate the direct and indirect effects as well as the total effect of each dimension of Alexithymia on Mobile phone addiction with the mediating role of stress, depression and anxiety. Statistical analysis was done by SPSS version 22 and Amos version 16 software. Results Alexithymia was a predictive factor for mobile phone addiction. Also, Alexithymia had a positive and significant effect on depression, anxiety and stress. Depression, anxiety and stress had a positive and significant effect on mobile phone addiction. Depression, anxiety and stress variables played the role of a relative mediating variable between Alexithymia and mobile phone addiction. Alexithymia through depression, anxiety and stress also has an indirect effect on Internet addiction. Conclusion Alexithymia is a predictive factor for mobile phone addiction; And the variables of depression, anxiety and stress play the role of a relative mediating variable between Alexithymia and mobile phone addiction.

Keywords: alexithymia, mobile phone, depression, anxiety, stress

Procedia PDF Downloads 97

Authors: Rasha F. Sharaf

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Administration of local anesthesia for a child is considered a painful procedure, which affects his vital signs, physiological parameters, and his further attitude in the dental clinic. During the extraction of mandibular molars, the nerve block technique is the most commonly used for the administration of local anesthesia; however, this technique requires deep penetration of the needle, which causes pain and discomfort for the child. Therefore, the inferior alveolar nerve block technique can be substituted with an infiltration technique which is not painful if a potent anesthetic solutions will be used. In the current study, the effect of Articaine 4% will be compared to Mepivacaine 2%, and their influence on the vital signs of the child, as well as their ability to control pain during extraction, will be assessed.

Keywords: anesthesia, articaine, pain control, extraction

Procedia PDF Downloads 121

Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Bahlouli Ahmed, Bentalab Nourdin, Nigrou Mourad

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This study was aimed at investigating the effect of orientation fiber reinforced on dynamic properties of laminate composite FRP. An experimental investigation is implemented using an impulse technique. The various specimens are excited in free vibration by the use of bi-channel Analyzer. The experimental results are compared by model of finite element analysis using ANSYS. The results studies (natural frequencies measurements, vibration mode, dynamic modulus and damping ratio) show that the effects of significant parameters such as lay-up and stacking sequence, boundary conditions and excitation place of accelerometer. These results are critically examined and discussed. The accuracy of these results is demonstrated by comparing results with those available in the literature.

Keywords: natural frequency, damping ratio, laminate composite, dynamic modulus

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Authors: Vikram Singh, Parmod Kumar Sethi

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The objective of the study was to study the effectiveness of common yoga protocol on reaction time (choice visual reaction time, measured in milliseconds/seconds) of male football players in the age group of 16 to 21 years. The 40 boys were measured initially on parameters of years of experience, level of participation. They were randomly assigned into two groups i.e. control and experimental. CVRT for both the groups was measured on day-1 and post intervention (common yoga protocol here) was measured after 45 days of training to the experimental group after they had finished with their regular fitness and soccer skill training. One way ANOVA (Univariate analysis) and Independent t-test using SPSS 23 statistical package were applied to get and analyze the results. The experimental yoga protocol group showed a significant reduction in CVRT, whereas the insignificant difference in reaction times was observed for control group after 45 days. The effect size was more than 52% for CVRT indicating that the effect of treatment was large. Power of the study was also found to be high (> .80). There was a significant difference after 45 days of yoga protocol in choice visual reaction time of experimental group (p = .000), t (21.93) = 6.410, p = .000 (two-tailed). The null hypothesis (that there would be no difference in reaction times of control and experimental groups) was rejected. Where p< .05. Therefore alternate hypothesis was accepted.

Keywords: reaction time, yoga protocol, t-test, soccer players

Procedia PDF Downloads 235

Authors: Abeer Ahmed Abdelhameed

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The aim of this study was to investigate the effect of aerobic exercises on LV parameters, lipid profile, and anthropometric measurements in hypertensive middle aged male subjects. Thirty obese patients were recruited for the study from the outpatient clinic of National Heart Institute, Egypt. Their ages ranges from 40 to 60 years. All participants underwent an aerobic training program including regular aerobic sub-maximal exercises in the form of treadmill walking and abdominal exercises 3/week for four months, the exercise were individually tailored for each participant depending on the result of cardiopulmonary exercise test. The result showed no significant difference observed in both LVPWT and LVSWT data from pre-test values to post-test values in all subjects after 4 months, with a significant reduction in WHR, systolic blood pressure, TAG and LDL records. Result also revealed a significant increase in HDL, Eƒ, LVEDD and FS records for all participants. The significant improvement in ventricular functions in form of ejection fraction of electrical group more than exercise group after 4 months at the end of the study may be due to the beneficial effect of faradic stimulation in lipolysis of storage adipose tissues, stimulation of lean body mass and muscles and/or thermal effect that improves vascularization.

Keywords: left ventricular parameters, aerobic training, electrical stimulation, lipid profile

Procedia PDF Downloads 252

Authors: Anna Sanczyk

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Diverse students may experience different forms of discrimination. Some of the oppression students experience in schools are racism, sexism, classism, or homophobia that may affect their achievement, and teachers need to make sure they create inclusive, equitable classroom environments. The broader literature on social change in education shows that teachers who challenge oppression and want to promote equitable and transformative education face institutional, social, and political constraints. This paper discusses research on teachers’ work to create socially just and culturally inclusive classrooms and schools. The practical contribution of this literature review is that it provides a comprehensive compilation of the studies presenting teachers’ roles and efforts in affecting social change. The examination of the research on social change in education points to the urgency of teachers addressing the needs of marginalized students and resisting systemic oppression in schools. The implications of this literature review relate to the concerns that schools should provide greater advocacy for marginalized students in diverse learning contexts, and teacher education programs should prepare teachers to be active advocates for diverse students. The literature review has the potential to inform educators to enhance educational equity and improve the learning environment. This literature review illustrates teachers as agents of change in diverse classrooms and contributes to understanding various ways of taking action towards fostering more equitable and transformative education in today’s schools.

Keywords: agents of change, diversity, opression, social change

Procedia PDF Downloads 139

Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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Authors: Adriana Duarte, Sandra Sampaio, Catia Ferreira, Jaime I. N. R. Gomes

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With the fashion of faded worn garments the textile industry has moved from indigo and pigments to dyes that are fixed by cationization, with products that can be toxic, and that can show this effect after washing down the dye with friction and/or treating with enzymes in a subsequent operation. Increasingly they are treated with bleaches, such as hypochlorite and permanganate, both toxic substances. An alternative process is presented in this work for both garment and jet dyeing processes, without the use of pre-cationization and the alternative use of “particle-dyes”. These are hybrid products, made up by an inorganic particle and an organic dye. With standard soluble dyes, it is not possible to avoid diffusion into the inside of the fiber unless using previous cationization. Only in this way can diffusion be avoided keeping the centre of the fibres undyed so as to produce the faded effect by removing the surface dye and showing the white fiber beneath. With “particle-dyes”, previous cationization is avoided. By applying low temperatures, the dye does not diffuse completely into the inside of the fiber, since it is a particle and not a soluble dye, being then able to give the faded effect. Even though bleaching can be used it can also be avoided, by the use of friction and enzymes they can be used just as for other dyes. This fashion brought about new ways of applying reactive dyes by the use of previous cationization of cotton, lowering the salt, and temperatures that reactive dyes usually need for reacting and as a side effect the application of a more environmental process. However, cationization is a process that can be problematic in applying it outside garment dyeing, such as jet dyeing, being difficult to obtain level dyeings. It also should be applied by a pad-fix or Pad-batch process due to the low affinity of the pre-cationization products making it a more expensive process, and the risk of unlevelness in processes such as jet dyeing. Wit particle-dyes, since no pre-cationizartion is necessary, they can be applied in jet dyeing. The excess dye is fixed by a fixing agent, fixing the insoluble dye onto the surface of the fibers. By applying the fixing agent only one to 1-3 rinses in water at room temperature are necessary, saving water and improving the washfastness.

Keywords: denim, garment dyeing, worn look, eco-fashion

Procedia PDF Downloads 537

Authors: Rachel Barker

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The exponential velocity in the truly knowledge-intensive world today has increasingly bombarded organizations with unfathomable challenges. Hence organizations are introduced to strange lexicons of descriptors belonging to a new paradigm of who, what and how knowledge at individual and organizational levels should be managed. Although organizational knowledge has been recognized as a valuable intangible resource that holds the key to competitive advantage, little progress has been made in understanding how knowledge sharing at individual level could benefit knowledge use at collective level to ensure added value. The research problem is that a lack of research exists to measure knowledge sharing through a multi-layered structure of ideas with at its foundation, philosophical assumptions to support presuppositions and commitment which requires actual findings from measured variables to confirm observed and expected events. The purpose of this paper is to address this problem by presenting a theoretical approach to measure knowledge sharing in emerging knowledge organizations. The research question is that despite the competitive necessity of becoming a knowledge-based organization, leaders have found it difficult to transform their organizations due to a lack of knowledge on who, what and how it should be done. The main premise of this research is based on the challenge for knowledge leaders to develop an organizational culture conducive to the sharing of knowledge and where learning becomes the norm. The theoretical constructs were derived and based on the three components of the knowledge management theory, namely technical, communication and human components where it is suggested that this knowledge infrastructure could ensure effective management. While it is realised that it might be a little problematic to implement and measure all relevant concepts, this paper presents effect of eight critical success factors (CSFs) namely: organizational strategy, organizational culture, systems and infrastructure, intellectual capital, knowledge integration, organizational learning, motivation/performance measures and innovation. These CSFs have been identified based on a comprehensive literature review of existing research and tested in a new framework adapted from four perspectives of the balanced score card (BSC). Based on these CSFs and their items, an instrument was designed and tested among managers and employees of a purposefully selected engineering company in South Africa who relies on knowledge sharing to ensure their competitive advantage. Rigorous pretesting through personal interviews with executives and a number of academics took place to validate the instrument and to improve the quality of items and correct wording of issues. Through analysis of surveys collected, this research empirically models and uncovers key aspects of these dimensions based on the CSFs. Reliability of the instrument was calculated by Cronbach’s a for the two sections of the instrument on organizational and individual levels.The construct validity was confirmed by using factor analysis. The impact of the results was tested using structural equation modelling and proved to be a basis for implementing and understanding the competitive predisposition of the organization as it enters the process of knowledge management. In addition, they realised the importance to consolidate their knowledge assets to create value that is sustainable over time.

Keywords: innovation, intellectual capital, knowledge sharing, performance measures

Procedia PDF Downloads 195

Authors: Daniel R. dos Santos, Mateus S. Maldonado, Estevão J. R. Batista

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The military commanders increasingly dependent on spatial awareness, as knowing where enemy are, understanding how war battle scenarios change over time, and visualizing these trends in ways that offer insights for decision-making. Thanks to advancements in geospatial technologies and artificial intelligence algorithms, the commanders are now able to modernize military operations on a universal scale. Thus, geovisualisation has become an essential asset in the defense sector. It has become indispensable for better decisionmaking in dynamic/temporal scenarios, operation planning and management for the war field, situational awareness, effective planning, monitoring, and others. For example, a 3D visualization of war field data contributes to intelligence analysis, evaluation of postmission outcomes, and creation of predictive models to enhance decision-making and strategic planning capabilities. However, old-school visualization methods are slow, expensive, and unscalable. Despite modern technologies in generating 3D point clouds, such as LIDAR and stereo sensors, monocular depth values based on deep learning can offer a faster and more detailed view of the environment, transforming single images into visual information for valuable insights. We propose a dedicated monocular depth reconstruction approach via deep learning techniques for 3D geovisualisation of satellite images. It introduces scalability in terrain reconstruction and data visualization. First, a dataset with more than 7,000 satellite images and associated digital elevation model (DEM) is created. It is based on high resolution optical and radar imageries collected from Planet and Copernicus, on which we fuse highresolution topographic data obtained using technologies such as LiDAR and the associated geographic coordinates. Second, we developed an imagery-DEM fusion strategy that combine feature maps from two encoder-decoder networks. One network is trained with radar and optical bands, while the other is trained with DEM features to compute dense 3D depth. Finally, we constructed a benchmark with sparse depth annotations to facilitate future research. To demonstrate the proposed method's versatility, we evaluated its performance on no annotated satellite images and implemented an enclosed environment useful for Geovisualisation applications. The algorithms were developed in Python 3.0, employing open-source computing libraries, i.e., Open3D, TensorFlow, and Pythorch3D. The proposed method provides fast and accurate decision-making with GIS for localization of troops, position of the enemy, terrain and climate conditions. This analysis enhances situational consciousness, enabling commanders to fine-tune the strategies and distribute the resources proficiently.

Keywords: depth, deep learning, geovisualisation, satellite images

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Authors: Ghandehari-Motlagh, Mohammad

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Purpose: To evaluate of the effect of an ideal fit of RGPs on HOA and keratoconus indices. Methods: In this cohort study, 65 keratoconus eyes with more than 3 lines(Snellen)improvement between BSCVA and BCVA(RGP) were imaged with Pentacam HR and their topometric and Zernike analysis findings without RGP were recorded. After 6 months or later of RGP fitting (Rose-K,Boston XO2), imaging with pentacam was repeated and the above information were recorded. Results: 65 different grades of keratoconus eyes with mean age of 27.32 yrs/old(SD +_5.51)enrolled including M 28(43.1%) and F 37(56.9%). 44(67.7%) with family Hx of Kc and 21(31.25%)without any Kc in their families. 54 (83.1%) with and 11 (16.9%) without any ocular allergy Hx. Maximum percent of age of onset of kc was 15 ys/old(29.2%).This study showed there are meaningful correlations between with and without RGP Pentacam indices and HOA in each grade of Kc.92.3% of patients had foreign body sensation but 96.9% had 11-20 hours/day RGP wear that confirms on psychologic effect of an ideal fit on patient’s motivation. Conclusion: With the three points touch principle of RGP fitting in Kc corneas, the patients will have a decrease in HOA and so delayed need for PK or LK.

Keywords: keratoconus, rigid gas permeable lens, aberration, fitting

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Authors: Selinda England, Ben Bodnaryk

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With an unprecedented increase in provincial immigration and government support for greater international and culturally diverse learners, a trade/applied learning-focused polytechnic with four campuses within one Canadian province saw the need for intercultural awareness and an intercultural teaching competence strategy for faculty training. An institution-wide pre-assessment needs survey was conducted in 2018, in which 87% of faculty professed to have some/no training when working with international and/or culturally diverse learners. After researching fellow Polytechnics in Canada and seeing very little in the way of faculty support for intercultural competence, an institutional project team comprised of members from all facets of the Polytechnic was created and included: Indigenous experts, Academic Chairs, Directors, Human Resource Managers, and international/settlement subject matter experts. The project team was organized to develop and implement a new academic model focused on enriching intercultural competence among faculty. Utilizing a competency based model, the project team incorporated inclusive terminology into competency indicators and devised a four-phase proposal for implementing intercultural teacher training: a series of workshops focused on the needs of international and culturally diverse learners, including teaching strategies based on current TESOL methodologies, literature and online resources for quick access when planning lessons, faculty assessment examples and models of interculturally proficient instructors, and future job descriptions - all which promote and encourage development of specific intercultural skills. Results from a post-assessment survey (to be conducted in Spring 2020) and caveats regarding improvements and next steps will be shared. The project team believes its intercultural and inclusive teaching competency-based model is one of the first, institution-wide faculty supported initiatives within the Canadian college and Polytechnic post-secondary educational environment; it aims to become a leader in both the province and nation regarding intercultural competency training for trades, industry, and business minded community colleges and applied learning institutions.

Keywords: cultural diversity and education, diversity training teacher training, teaching and learning, teacher training

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Authors: Hyeon-Seong Kim, Sang-Mi Park, Seul-Gi Kim, Seon-Ju Han, Leen-Seok Kang

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The use of BIM, including 4D CAD system, in a construction project is gradually increasing. Since the building construction works repeatedly in the vertical space, it is relatively easy to confirm the interference effect when applying the BIM, but the interference effect for the civil engineering project is relatively small because the civil works perform non-repetitive processes in the horizontal space. For this reason, it is desirable to apply BIM to the construction phase when applying BIM to the civil engineering project, and the most active BIM tool applied to the construction phase is the 4D CAD function for the schedule management. This paper proposes the application procedure of BIM by the construction phase of civil engineering project and a linear 4D CAD construction methodology suitable for the civil engineering project in which linear work is performed.

Keywords: BIM, 4D CAD, linear 4D simulation, VR

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Authors: Manfred F. Maute, Olga Naumenko, Raymond T. Kong

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Using data from a nationally representative financial panel of Canadian households, this study develops a psychographic segmentation of the customers of a value-expressive credit card service and tests for effects on relational response differences. The variety of segments elicited by agglomerative and k means clustering and the familiar profiles of individual clusters suggest that the face validity of the psychographic segmentation was quite high. Segmentation had a significant effect on customer satisfaction and relationship depth. However, when socio-demographic characteristics like household size and income were accounted for in the psychographic segmentation, the effect on relational response differences was magnified threefold. Implications for the segmentation of financial services markets are considered.

Keywords: customer satisfaction, financial services, psychographics, response differences, segmentation

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Authors: Jubee Varghese, Pouria Hafiz

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Increased use of lightweight concrete in the construction industry is mainly due to its reduction in the weight of the structural elements, which in turn reduces the cost of production, transportation, and the overall project cost. However, the structural application of these lightweight concrete structures is limited due to its reduced density. Hence, further investigations are in progress to study the effect of fiber inclusion in improving the mechanical properties of lightweight concrete. Incorporating structural steel fibers, in general, enhances the performance of concrete and increases its durability by minimizing its potential to cracking and providing crack arresting mechanism. In this research, Geometric and Materially Non-linear Analysis (GMNA) was conducted for Finite Element Modelling using a software known as ABAQUS, to investigate the structural behavior of lightweight concrete with and without the addition of steel fibers and shear reinforcement. 21 finite element models of beams were created to study the effect of steel fibers based on three main parameters; fiber volume fraction (Vf = 0, 0.5 and 0.75%), shear span to depth ratio (a/d of 2, 3 and 4) and ratio of area of shear stirrups to spacing (As/s of 0.7, 1 and 1.6). The models created were validated with the previous experiment conducted by H.K. Kang et al. in 2011. It was seen that the lightweight fiber reinforcement can replace the use of fiber reinforced normal weight concrete as structural elements. The effect of an increase in steel fiber volume fraction is dominant for beams with higher shear span to depth ratio than for lower ratios. The effect of stirrups in the presence of fibers was very negligible; however; it provided extra confinement to the cracks by reducing the crack propagation and extra shear resistance than when compared to beams with no stirrups.

Keywords: ABAQUS, beams, fiber-reinforced concrete, finite element, light weight, shear span-depth ratio, steel fibers, steel-fiber volume fraction

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Authors: Ajay Likhite, Prashant Parhad, D. R. Peshwe, S. U. Pathak

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Chromium bearing Austempered Ductile Iron (ADI) has been recently in the news for its improved wear performance over the ADI. The work presented below was taken up to study the effect of different austenitisation temperatures on the microstructure and wear performance of the Carbidic Austempered Ductile Iron (CADI). In this investigation Cr bearing ductile iron was subjected to austempering treatment to obtain an ausferritic microstructure. Two different austenitisation temperatures were selected whereas, the austempering temperature and time was kept unchanged. Microstructure and wear performance of this alloy, austenitized at two different temperatures was studied.

Keywords: austempered ductile iron, carbidic austempered ductile iron, austenitization temperature, wear behavior

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Authors: Gul Muhammad, Amanullah Marri, Asif Abbas

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Thermal treatment changes the physical and mechanical properties of clayey soils. Thermally treated soils have been used since ancient times for making trails for access and bricks for residence. In this study, it has been focused to observe and analyze the effect of baking (burning) temperature on the mechanical properties of clayey soils usually used for the construction of adobe houses in the rural areas of many of the developing countries. In the first stage of experimental work, a series of tests on clayey soil moulds (100 mm height and 50 mm diameter in size) added different percentages of lime and wheat straw (typically 2%, 4%, 6%, 8%, and 10%) were conducted. In the second stage; samples were made of clayey soils and were subjected to six level of temperatures i.e., 25, 100, 200, 300, 400, and 500⁰C. In the third stage, the moulds of clayey soil were submerged in water prior to testing in order to investigate the flood resilience of the moulds prepared with and without the addition of lime and wheat straw. The experimental results suggest that samples with 6% of lime content and on 2% of wheat straw contents have shown the maximum value of compressive strength. The effect of baking temperature on the clayey soils has shown that maximum UCS is obtained at 200⁰C. The results also suggest reinforcement with 2% wheat straw, give 70.8% increase in the compressive strength compared to soil only, whereas the flooding resilience can be better resist by adding 6% lime and 2% wheat straw.

Keywords: baked temperature, submersion, lime, uniaxial, wheat straw

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Authors: Jana Beresova

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The paper presents a study carried out in 2015-2016 within the national scheme of research - VEGA 1/0106/15 based on theoretical research and empirical verification of the concept of intercultural communicative competence. It focuses on the current conception concerning target languages teaching compatible with the Common European Framework of Reference for Languages: Learning, teaching, assessment. Our research had revealed how the concept of intercultural communicative competence had been perceived by secondary-school teachers of English in Slovakia before they were intensively trained. Intensive workshops were based on the use of both authentic and instructional materials with the goal to support interculturally oriented language teaching aimed at challenging thinking. The former concept that supported the development of the students´ linguistic knowledge and the use of a target language to obtain information about the culture of the country whose language learners were learning was expanded by the meaning-making framework which views language as a typical means by which culture is mediated. The goal of the workshop was to influence English teachers to better understand the concept of intercultural communicative competence, combining theory and practice optimally. The results of the study will be presented and analysed, providing particular recommendations for language teachers and suggesting some changes in the National Educational Programme from which English learners should benefit in their future studies or professional careers.

Keywords: authentic materials, English language teaching, instructional materials, intercultural communicative competence

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Authors: Fengjuan Wang, Azilawati Jamaludin

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Developmental Dyscalculia (DD) is defined as a particular learning difficulty with continuous challenges in learning requisite math skills that cannot be explained by intellectual disability or educational deprivation. Recent studies have increasingly recognized that DD is a heterogeneous, instead of monolithic, learning disorder with not only cognitive and behavioral deficits but so too neural dysfunction. In recent years, neuroimaging studies employed group comparison to explore the neural underpinnings of DD, which contradicted the heterogenous nature of DD and may obfuscate critical individual differences. This research aimed to investigate the neural heterogeneity of DD using case studies with functional near-infrared spectroscopy (fNIRS). A total of 54 aged 6-7 years old of children participated in this study, comprising two comprehensive cognitive assessments, an 8-minute resting state, and an 8-minute one-digit addition task. Nine children met the criteria of DD and scored at or below 85 (i.e., the 16th percentile) on the Mathematics or Math Fluency subtest of the Wechsler Individual Achievement Test, Third Edition (WIAT-III) (both subtest scores were 90 and below). The remaining 45 children formed the typically developing (TD) group. Resting-state data and brain activation in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), and intraparietal sulcus (IPS) were collected for comparison between each case and the TD group. Graph theory was used to analyze the brain network under the resting state. This theory represents the brain network as a set of nodes--brain regions—and edges—pairwise interactions across areas to reveal the architectural organizations of the nervous network. Next, a single-case methodology developed by Crawford et al. in 2010 was used to compare each case’s brain network indicators and brain activation against 45 TD children’s average data. Results showed that three out of the nine DD children displayed significant deviation from TD children’s brain indicators. Case 1 had inefficient nodal network properties. Case 2 showed inefficient brain network properties and weaker activation in the IFG and IPS areas. Case 3 displayed inefficient brain network properties with no differences in activation patterns. As a rise above, the present study was able to distill differences in architectural organizations and brain activation of DD vis-à-vis TD children using fNIRS and single-case methodology. Although DD is regarded as a heterogeneous learning difficulty, it is noted that all three cases showed lower nodal efficiency in the brain network, which may be one of the neural sources of DD. Importantly, although the current “brain norm” established for the 45 children is tentative, the results from this study provide insights not only for future work in “developmental brain norm” with reliable brain indicators but so too the viability of single-case methodology, which could be used to detect differential brain indicators of DD children for early detection and interventions.

Keywords: brain activation, brain network, case study, developmental dyscalculia, functional near-infrared spectroscopy, graph theory, neural heterogeneity

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Authors: Sahithi Yarlagadda

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The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

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Authors: Nodelman V.

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Despite serious difficulties in the assimilation of the conceptual system of Calculus, software in the educational process is used only occasionally, and even then, mainly for illustration purposes. The following are a few reasons: The non-trivial nature of the studied material, Lack of skills in working with software, Fear of losing time working with software, The variety of the software itself, the corresponding interface, syntax, and the methods of working with the software, The need to find suitable models, and familiarize yourself with working with them, Incomplete compatibility of the found models with the content and teaching methods of the studied material. This paper proposes an active use of the developed non-commercial software VusuMatica, which allows removing these restrictions through Broad support for the studied mathematical material (and not only Calculus). As a result - no need to select the right software, Emphasizing the unity of mathematics, its intrasubject and interdisciplinary relations, User-friendly interface, Absence of special syntax in defining mathematical objects, Ease of building models of the studied material and manipulating them, Unlimited flexibility of models thanks to the ability to redefine objects, which allows exploring objects characteristics, and considering examples and counterexamples of the concepts under study. The construction of models is based on an original approach to the analysis of the structure of the studied concepts. Thanks to the ease of construction, students are able not only to use ready-made models but also to create them on their own and explore the material studied with their help. The presentation includes examples of using VusuMatica in studying the concepts of limit and continuity of a function, its derivative, and integral.

Keywords: counterexamples, limitations and requirements, software, teaching and learning calculus, user-friendly interface and syntax

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Authors: Aimen Mohamed Almaloul

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The main focus of this study is investigating the interference of Arabic in the use of English prepositions by Libyan university students. Prepositions in the tests used in the study were categorized, according to their relation to Arabic, into similar Arabic and English prepositions (SAEP), dissimilar Arabic and English prepositions (DAEP), Arabic prepositions with no English counterparts (APEC), and English prepositions with no Arabic counterparts (EPAC). The subjects of the study were the first year university students of the English department, Sabrata Faculty of Arts, Azzawia University; both males and females, and they were 100 students. The basic tool for data collection was a test of English prepositions; students are instructed to fill in the blanks with the correct prepositions and to put a zero (0) if no preposition was needed. The test was then handed to the subjects of the study. The test was then scored and quantitative as well as qualitative results were obtained. Quantitative results indicated the number, percentages and rank order of errors in each of the categories and qualitative results indicated the nature and significance of those errors and their possible sources. Based on the obtained results the researcher could detect that students made more errors in the EPAC category than the other three categories and these errors could be attributed to the lack of knowledge of the different meanings of English prepositions. This lack of knowledge forced the students to adopt what is called the strategy of transfer.

Keywords: foreign language acquisition, foreign language learning, interference system, interlanguage system, mother tongue interference

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Authors: Nail Nazarov, Vladimir Zobov, Alexandra Vyshtakalyuk, Vyacheslav Semenov, Irina Galyametdinova, Vladimir Reznik

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There have been studied effects of xymedon and six new pyrimidine derivatives, that are close and distant analogs of xymedon, on rats' working capacity in the test 'swimming to failure'. It has been shown that a single administration of the studied compounds did not have a statistically significant effect in the test. In the conditions of multiple intraperitoneal administration of the studied pyrimidine derivatives, the compound L-ascorbate, 1-(2-hydroxyethyl)-4.6-dimethyl-1.2-dihydropyrimidine-2-one had the lowest toxicity and the most pronounced actoprotective effect. Introduction in the dose of 20 mg/kg caused a statistically significant increase 440 % in the duration of swimming of rats on the 14th day of the experiment compared with the control group. Multiple administration of the compound in the conditions of physical load did not affect leucopoiesis but stimulates erythropoiesis resulting in an increase in the number of erythrocytes and a hemoglobin level. The substance introduction under mixed exhausting loads prevented such changes of blood biochemical parameters as reduction of glucose, increased of urea and lactic acid levels, what indicates improvement in the animals' tolerability of loads and an anti-catabolic effect of the compound. Absence of hepato and cardiotoxic effects of the substance has been shown. This work was performed with the financial support of Russian Science Foundation (grant № 14-50-00014).

Keywords: actoprotectors, physical working capacity, pyrimidine derivatives, xymedon

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Authors: Yilin Liao, Hewen Li, Paula McConvey

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Speed skaters often face a risk of concussion when they fall on the ice floor and impact crash mats during practices and competitive races. Several variables, including those related to the skater, the crash mat, and the impact position (body side/head/feet impact), are believed to influence the severity of the skater's concussion. While computer simulation modeling can be employed to analyze these accidents, the simulation process is time-consuming and does not provide rapid information for coaches and teams to assess the skater's injury risk in competitive events. This research paper promotes the exploration of the feasibility of using AI techniques for evaluating skater’s potential concussion severity, and to develop a fast concussion prediction tool using artificial neural networks to reduce the risk of treatment delays for injured skaters. The primary data is collected through virtual tests and physical experiments designed to simulate skater-mat impact. It is then analyzed to identify patterns and correlations; finally, it is used to train and fine-tune the artificial neural networks for accurate prediction. The development of the prediction tool by employing machine learning strategies contributes to the application of AI methods in sports science and has theoretical involvements for using AI techniques in predicting and preventing sports-related injuries.

Keywords: artificial neural networks, concussion, machine learning, impact, speed skater

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Authors: Elizabeth Spink

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Providing safe and affordable drinking water to low-income households in developing countries remains a challenge. Policy goals of increasing household piped-water access and cost recovery for utility providers are often at odds. Nonpayment of utility bills is frequently cited as a constraint to improving the quality of utility service. However, nonpayment is widely tolerated, and households often accumulate significant debt to the utility provider. This study examines the effect of enforcement of water bill payment through supply disconnections in Livingstone, Zambia. This research uses a dynamic model of household monthly payments and accumulation of arrears, which determine the probability of disconnection, and simulates the effect of exogenous changes in enforcement levels. This model is empirically tested using an event-study framework of exogenous increases in enforcement capacity that occur during administrative rezoning events, which reduce the number of households that one enforcement agent is responsible for. The results show that households are five percentage points more likely to make a payment in the months following a rezoning event, but disconnections for low-income households increase as well, resulting in little change in revenue collected by the water utility. The results suggest that high enforcement of water bill payments toward credit-constrained households may be ineffective and lead to reduced piped-water access.

Keywords: enforcement, nonpayment, piped-water access, water utilities

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