Search results for: effect of collaborative learning
16681 Effects of Classroom Management Strategies on Students’ Well-Being at Secondary Level
Authors: Saba Latif
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The study is about exploring the Impact of Classroom Management Techniques on students’ Well-being at the secondary level. The objectives of the study are to identify the classroom management practices of teachers and their impact on students’ achievement. All secondary schools of Lahore city are the population of study. The researcher randomly selected ten schools, and from these schools, two hundred students participated in this study. Data has been collected by using Classroom Management and Students’ Wellbeing questionnaire. Frequency analysis has been applied. The major findings of the study are calculated as follows: The teacher’s instructional activities affect classroom management. The secondary school students' seating arrangement can influence the learning-teaching process. Secondary school students strongly disagree with the statement that the large size of the class affects the teacher’s classroom management. The learning environment of the class helps students participate in question-and-answer sessions. All the activities of the teachers are in accordance with practices in the class. The discipline of the classroom helps the students to learn more. The role of the teacher is to guide, and it enhances the performance of the teacher. The teacher takes time on disciplinary rules and regulations of the classroom. The teacher appreciates them when they complete the given task. The teacher appreciates teamwork in the class.Keywords: classroom management, strategies, wellbeing, practices
Procedia PDF Downloads 4316680 Enhancing a Recidivism Prediction Tool with Machine Learning: Effectiveness and Algorithmic Fairness
Authors: Marzieh Karimihaghighi, Carlos Castillo
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This work studies how Machine Learning (ML) may be used to increase the effectiveness of a criminal recidivism risk assessment tool, RisCanvi. The two key dimensions of this analysis are predictive accuracy and algorithmic fairness. ML-based prediction models obtained in this study are more accurate at predicting criminal recidivism than the manually-created formula used in RisCanvi, achieving an AUC of 0.76 and 0.73 in predicting violent and general recidivism respectively. However, the improvements are small, and it is noticed that algorithmic discrimination can easily be introduced between groups such as national vs foreigner, or young vs old. It is described how effectiveness and algorithmic fairness objectives can be balanced, applying a method in which a single error disparity in terms of generalized false positive rate is minimized, while calibration is maintained across groups. Obtained results show that this bias mitigation procedure can substantially reduce generalized false positive rate disparities across multiple groups. Based on these results, it is proposed that ML-based criminal recidivism risk prediction should not be introduced without applying algorithmic bias mitigation procedures.Keywords: algorithmic fairness, criminal risk assessment, equalized odds, recidivism
Procedia PDF Downloads 14316679 Walmart Sales Forecasting using Machine Learning in Python
Authors: Niyati Sharma, Om Anand, Sanjeev Kumar Prasad
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Assuming future sale value for any of the organizations is one of the major essential characteristics of tactical development. Walmart Sales Forecasting is the finest illustration to work with as a beginner; subsequently, it has the major retail data set. Walmart uses this sales estimate problem for hiring purposes also. We would like to analyzing how the internal and external effects of one of the largest companies in the US can walk out their Weekly Sales in the future. Demand forecasting is the planned prerequisite of products or services in the imminent on the basis of present and previous data and different stages of the market. Since all associations is facing the anonymous future and we do not distinguish in the future good demand. Hence, through exploring former statistics and recent market statistics, we envisage the forthcoming claim and building of individual goods, which are extra challenging in the near future. As a result of this, we are producing the required products in pursuance of the petition of the souk in advance. We will be using several machine learning models to test the exactness and then lastly, train the whole data by Using linear regression and fitting the training data into it. Accuracy is 8.88%. The extra trees regression model gives the best accuracy of 97.15%.Keywords: random forest algorithm, linear regression algorithm, extra trees classifier, mean absolute error
Procedia PDF Downloads 14416678 Indigo Production in a Fed Batch Bioreactor Using Aqueous-Solvent Two Phase System
Authors: Vaishnavi Unde, Srikanth Mutnuri
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Today dye stuff sector is one of the major chemical industries in India. Indigo is a blue coloured dye used all over the world in large quantity. The indigo dye produced and used in textile industries is synthetic having toxic effect, thus there is an increase in interest for natural dyes owing to the environmental concerns. The present study focuses on the use of a strain Pandoraea sp. isolated from garage soil, for the production of indigo in fed batch bioreactor. A comparative study between single phase and two phase production was carried out in this work. The blue colour produced during the experiments was analyzed using, TLC, UV-visible spectrophotometer and FTIR technique. The blue pigment was found to be indigo. The production of bio-indigo was done in a single phase fermentor carrying medium and substrate indole in dissolved form and was found to produce maximum of 0.041 g/L of indigo. Whereas there was an increase in production of indigo to 0.068 g/L in a two phase, water-silicone oil system. In this study the advantage of using second phase as silicone oil has enhanced the indigo production, as the second phase made the substrate available to the bacteria by increasing the surface area as well as it helped to prevent the inhibition effect of the high concentration of substrate, indole. The effect of single and two phases on the growth of bacteria was also studied.Keywords: dyes, fed batch reactor, indole, Indigo
Procedia PDF Downloads 43016677 Evaluation of Corrosion by Impedance Spectroscopy of Embedded Steel in an Alternative Concrete Exposed a Chloride Ion
Authors: E. Ruíz, W. Aperador
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In this article evaluates the protective effect of the concrete alternative obtained from the fly ash and iron and steel slag mixed in binary form and were placed on structural steel ASTM A 706. The study was conducted comparatively with specimens exposed to natural conditions free of chloride ion. The effect of chloride ion on the specimens was generated of form accelerated under controlled conditions (3.5% NaCl and 25 ° C temperature). The Impedance data were acquired over a range of 1 mHz to 100 kHz. At frequencies high is found the response of the interface means of the exposure-concrete and to frequency low the response of the interface corresponding to concrete-steel.Keywords: alternative concrete, corrosion, alkaline activation, impedance spectroscopy
Procedia PDF Downloads 35316676 Creativity and Intelligence: Psychoeducational Connections
Authors: Cristina Costa-Lobo, Carla B. Vestena, Filomena E. Ponte
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Creativity and intelligence are concepts that have aroused very expressive interest in the field of educational sciences and the field of psychological science since the middle of the last century since they have a great impact on the potential and well-being of individuals. However, due to progress in cognitive and positive psychology, there has been a growing interest in the psychoeducational domain of intelligence and creativity in the last decade. In this theoretical work, are analyzed comparatively the theoretical models that relate the intelligence and the creativity, are analyzed several psychoeducational intervention programs that have been implemented with a view to the promotion of creativity and signal possibilities, realities and ironies around the psychological evaluation of intelligence and creativity. In order to reach a broad perspective on creativity, the evidence is presented that points the need to evaluate different psychological domains. The psychoeducational intervention programs addressed have, with a common characteristic, the full stimulation of the creative potential of the participants, assumed as a highly valued capacity at the present time. The results point to the systematize that all interventions in the ambit of creativity have two guiding principles: all individuals can be creative, and creativity is a capacity that can be stimulated. This work refers to the importance of stimulus creativity in educational contexts, to the usefulness and pertinence of the creation, the implementation, and monitoring of flexible curricula, adapted to the educational needs of students, promoting a collaborative work among teachers, parents, students, psychologists, managers and educational administrators.Keywords: creativity, intelligence, psychoeducational intervention programs, psychological evaluation, educational contexts
Procedia PDF Downloads 39816675 Storage of Maize Grains Using Powder and Oils of Commonly Used Medicinal Plants (Aframomum melegueta, Garcinia kola and Piper guineense)
Authors: T. O. Adejumo, O. S. Akinyemi
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Powders and oils of Aframomum melegueta, Garcinia kola and Piper guineense were tested as preservatives for the storage of maize grains for four weeks. The concentrations of the powders were 32.5gkg-1, 65.0gkg-1 and 97.5gkg-1 maize, while those of oils were 0.85mlkg-1, 0.50mlkg-1 and 0.75mlkg-1 maize respectively. Powders of the three botanicals at 97.5gkg-1 maize possessed insecticidal effect on Sitophilus zeamais and also inhibitory activities on Aspergillus flavus, A. fumigatus, A. niger and Fusarium verticillioides, while little effect was observed for other concentrations. Oils of the three botanicals at 0.50mlkg-1 and 0.75mlkg-1 maize showed an insecticidal effect on S. zeamais and also inhibitory activities on A. flavus, A. fumigatus, A. niger, F. verticillioides, Penicillium and Rhizopus species. Oils showed more potential as a protectant against fungal and insect pest in storage maize grains than powders. Powders and oils of A. melegueta, G. kola and P. guineense could be successfully used as biopesticides.Keywords: aframomum melegueta, garcinia kola, maize, powder, oils, piper guineense
Procedia PDF Downloads 39416674 Oi̇l Absorption Behavior and Its Effect on Charpy Impact Test of Glass Reinforced Polyester Composites Used in the Manufacture of Naval Ship Hulls
Authors: Bouhafara Djaber, Menail Younes, Mesrafet Farouk, Aissaoui Mohammed Islem
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This article presents results of experimental investigations of the durability of (GFRP) composite exposed to typical environments of marine industries applications,The use of fiber-glass reinforced polyester composites in marine applications such as Hulls of voyage boats and hulls of small vessels for the military navy , this type of composite is becoming attractive because of their reduced weight and improved corrosion resistance. However,a deep understating of oil ageing effect on composite structures is essential to ensure long-term performance and durability. in this work evaluate the effect of oil ageing on absorptıon behavıor and ımpact properties of glass/polyester composites manufactured with two types of fiber fabrics (fibreglass mat and fiberglass woven roving) and isophthalic polyester resin. The specimens obtained from commercial (GFRP) profiles made of unsaturated polyester resin were subjected to immersion in (i) marine oil for boats and (ii) salt water at ambient temperature for up to 1 month. The effects of such exposure conditions on this types of profile we analysed in what concerns their (i) mass change,(ii) mechanical response in impact, namely on the mechanical response – oil immersion caused a higher level of degradation, compared with salt water immersion;fracture surface examination by scanning electron microscopy revealed delamination, fiber debonding and resin crumbling due to oil effect.Keywords: Marine Engine Oil, Absorption, Polyester, Glass Fibre
Procedia PDF Downloads 7316673 Exploring Students’ Voices in Lecturers’ Teaching and Learning Developmental Trajectory
Authors: Khashane Stephen Malatji, Makwalete Johanna Malatji
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Student evaluation of teaching (SET) is the common way of assessing teaching quality at universities and tracing the professional growth of lecturers. The aim of this study was to investigate the role played by student evaluation in the teaching and learning agenda at one South African University. The researchers used a qualitative approach and a case study research design. With regards to data collection, document analysis was used. Evaluation reports were reviewed to monitor the growth of lecturers who were evaluated during the academic years 2020 and 2021 in one faculty. The results of the study reveal that student evaluation remains the most relevant tool to inform the teaching agenda at a university. Lecturers who were evaluated were found to grow academically. All lecturers evaluated during 2020 have shown great improvement when evaluated repeatedly during 2021. Therefore, it can be concluded that student evaluation helps to improve the pedagogical and professional proficiency of lecturers. The study therefore, recommends that lecturers conduct an evaluation for each module they teach every semester or annually in case of year modules. The study also recommends that lecturers attend to all areas that draw negative comments from students in order to improve.Keywords: students’ voices, teaching agenda, evaluation, feedback, responses
Procedia PDF Downloads 8616672 AI for Efficient Geothermal Exploration and Utilization
Authors: Velimir "monty" Vesselinov, Trais Kliplhuis, Hope Jasperson
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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal
Procedia PDF Downloads 4016671 Some Fundamental Physical Properties of BiGaO₃ Cubic Perovskite
Authors: B. Gueridi, T. Chihi, M. Fatmi, A. Faci
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Some fundamental physical properties of BiGaO₃ were investigated under pressure and temperature effect using generalized gradient approximation and local density approximation approaches. The effect of orientation on Debye temperature and sound waves velocities were estimated from elastic constants. The value of the bulk modulus of BiGaO₃ is a sign of its high hardness because it is linked to an isotropic deformation. BiGaO₃ is a semiconductor and ductile material with covalent bonding (Ga–O), and the Bi-O bonding is ionic. The optical transitions were observed when electrons pass from the top of the valence band (O-2p) to the bottom of the conduction band (Ga-4p or Bi-6p). The thermodynamic parameters are determined in temperature and pressure ranging from 0 to 1800 K and 0 to 50 GPa.Keywords: BiGaO₃ perovskite, optical absorption, first principle, band structure
Procedia PDF Downloads 11016670 Deep Learning for Image Correction in Sparse-View Computed Tomography
Authors: Shubham Gogri, Lucia Florescu
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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net
Procedia PDF Downloads 15016669 Aging Effect on Mechanical Behavior of Duplex Stainless Steel
Authors: Jeonho Moon, Tae Kwon Ha
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In the present study, the effect of Si, Al, Ti, Zr, and Nb addition on the microstructure and hot workability of cast M42 tool steels, basically consisting of 1.0 C, 0.2 Mn, 3.8 Cr, 1.5 W, 8.5 Co, 9.2 Mo, and 1.0 V in weight percent has been investigated. Tool steels containing Si of 0.25 and 0.5 wt.%, Al of 0.06 and 0.12 wt.%, Ti of 0.3 wt.%, Zr of 0.3 wt.%, and Nb of 0.3wt.% were cast into ingots of 140 mm x 140 mm x 330 mm by vacuum induction melting. After solution treatment at 1150 °C for 1.5 hr followed by furnace cooling, hot rolling at 1180 °C was conducted on the ingots. Addition of titanium, zirconium and niobium was found to retard the decomposition of the eutectic carbides and result in the deterioration of hot workability of the tool steels, while addition of aluminum and silicon showed relatively well decomposed carbide structure and resulted in sound hot rolled plates.Keywords: duplex stainless steel, alloying elements, eutectic carbides, microstructure, hot workability
Procedia PDF Downloads 41416668 Unfolding Simulations with the Use of Socratic Questioning Increases Critical Thinking in Nursing Students
Authors: Martha Hough RN
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Background: New nursing graduates lack the critical thinking skills required to provide safe nursing care. Critical thinking is essential in providing safe, competent, and skillful nursing interventions. Educational institutions must provide a curriculum that improves nursing students' critical thinking abilities. In addition, the recent pandemic resulted in nursing students who previously received in-person clinical but now most clinical has been converted to remote learning, increasing the use of simulations. Unfolding medium and high-fidelity simulations and Socratic questioning are used in many simulations debriefing sessions. Methodology: Google Scholar was researched with the keywords: critical thinking of nursing students with unfolding simulation, which resulted in 22,000 articles; three were used. A second search was implemented with critical thinking of nursing students Socratic questioning, which resulted in two articles being used. Conclusion: Unfolding simulations increase nursing students' critical thinking, especially during the briefing (pre-briefing and debriefing) phases, where most learning occurs. In addition, the use of Socratic questions during the briefing phases motivates other questions, helps the student analyze and critique their thinking, and assists educators in probing students' thinking, which further increases critical thinking.Keywords: briefing, critical thinking, Socratic thinking, unfolding simulations
Procedia PDF Downloads 17416667 Sales-Based Dynamic Investment and Leverage Decisions: A Longitudinal Study
Authors: Rihab Belguith, Fathi Abid
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The paper develops a system-based approach to investigate the dynamic adjustment of debt structure and investment policies of the Dow-Jones index. This approach enables the assessment of relations among sales, debt, and investment opportunities by considering the simultaneous effect of the market environmental change and future growth opportunities. We integrate the firm-specific sales variance to capture the industries' conditions in the model. Empirical results were obtained through a panel data set of firms with different sectors. The analysis support that environmental change does not affect equally the different industry since operating leverage differs among industries and so the sensitivity to sales variance. Including adjusted-specific variance, we find that there is no monotonic relation between leverage, sales, and investment. The firm may choose a low debt level in response to high sales variance but high leverage to attenuate the negative relation between sales variance and the current level of investment. We further find that while the overall effect of debt maturity on leverage is unaffected by the level of growth opportunities, the shorter the maturity of debt is, the smaller the direct effect of sales variance on investment.Keywords: dynamic panel, investment, leverage decision, sales uncertainty
Procedia PDF Downloads 24016666 An Experimental Machine Learning Analysis on Adaptive Thermal Comfort and Energy Management in Hospitals
Authors: Ibrahim Khan, Waqas Khalid
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The Healthcare sector is known to consume a higher proportion of total energy consumption in the HVAC market owing to an excessive cooling and heating requirement in maintaining human thermal comfort in indoor conditions, catering to patients undergoing treatment in hospital wards, rooms, and intensive care units. The indoor thermal comfort conditions in selected hospitals of Islamabad, Pakistan, were measured on a real-time basis with the collection of first-hand experimental data using calibrated sensors measuring Ambient Temperature, Wet Bulb Globe Temperature, Relative Humidity, Air Velocity, Light Intensity and CO2 levels. The Experimental data recorded was analyzed in conjunction with the Thermal Comfort Questionnaire Surveys, where the participants, including patients, doctors, nurses, and hospital staff, were assessed based on their thermal sensation, acceptability, preference, and comfort responses. The Recorded Dataset, including experimental and survey-based responses, was further analyzed in the development of a correlation between operative temperature, operative relative humidity, and other measured operative parameters with the predicted mean vote and adaptive predicted mean vote, with the adaptive temperature and adaptive relative humidity estimated using the seasonal data set gathered for both summer – hot and dry, and hot and humid as well as winter – cold and dry, and cold and humid climate conditions. The Machine Learning Logistic Regression Algorithm was incorporated to train the operative experimental data parameters and develop a correlation between patient sensations and the thermal environmental parameters for which a new ML-based adaptive thermal comfort model was proposed and developed in our study. Finally, the accuracy of our model was determined using the K-fold cross-validation.Keywords: predicted mean vote, thermal comfort, energy management, logistic regression, machine learning
Procedia PDF Downloads 5516665 Application of GeoGebra into Teaching and Learning of Linear and Quadratic Equations amongst Senior Secondary School Students in Fagge Local Government Area of Kano State, Nigeria
Authors: Musa Auwal Mamman, S. G. Isa
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This study was carried out in order to investigate the effectiveness of GeoGebra software in teaching and learning of linear and quadratic equations amongst senior secondary school students in Fagge Local Government Area, Kano State–Nigeria. Five research items were raised in objectives, research questions and hypotheses respectively. A random sampling method was used in selecting 398 students from a population of 2098 of SS2 students. The experimental group was taught using the GeoGebra software while the control group was taught using the conventional teaching method. The instrument used for the study was the mathematics performance test (MPT) which was administered at the beginning and at the end of the study. The results of the study revealed that students taught with GeoGebra software (experimental group) performed better than students taught with traditional teaching method. The t- test was used to analyze the data obtained from the study.Keywords: GeoGebra Software, mathematics performance, random sampling, mathematics teaching
Procedia PDF Downloads 24316664 Effect of Different Arsenic Treatments on Root Growth of Sunflower Seedlings in Rhizobox Experiment
Authors: Szilvia Várallyay, Béla Kovács, Éva Bódi, Farzeneh Garousi, Szilvia Veres
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Arsenic (As) is a naturally occurring substance that can be present in soil, water and air. Vegetables, fruits, and other plants that grow in contaminated soils which are able to accumulate arsenic. Arsenic when presents in plant cells, has various negative physiological effects and when presents in soil will be inorgaic form, namely arsenite (As(III)) and arsenate (As(V)). These two forms of arsenic disrupt plant metabolism by inhibiting its growth and these arsenic species has negative effect on nutrient uptake. A rhizobox experiment was conducted to investigate the effect of arsenite and arsenate on root growth of sunflower seedlings. Sunflower plants were grown in climatic room under irradiance of 300 µmol m-2 s-1, 16-h day and 8-h night photoperiod, day/night temperature of 25/20°C and relative humidity of 65-75%. We applied arsenic in form of arsenite (NaAsO2) and arsenate (KH2AsO4), respectively. The applied arsenic treatments was 0, 10, 30, 90 mg.kg-1. After disinfection, seeds were germinated between moist filter papers. Seedlings with 2-3 cm coleoptils were placed into rhizoboxes. In the rhizoboxes the growing and daily growing rhythm of roots of sunflower can be followed up, moreover possible phytotoxic symptoms of roots resulting from increasing arsenic can be seen. Weights of rhizoboxes were measured daily and also evaporated water added each day. The lengths of roots were measured daily until seedlings roots get at the end of the rhizoboxes. Negative correlation was observed between the higher concentration of arsenic in the soil and the growth of sunflower seedlings roots. The effect of arsenic toxicity was more considerable in 90 mg.kg-1 arsenic treatment than lower concentration. The same arsenite concentration causes slower growth in case of sunflower plant than the same arsenate concentration produced.Keywords: arsenic, rhizobox experiment, sunflower, root growth
Procedia PDF Downloads 41116663 The Effect of MOOC-Based Distance Education in Academic Engagement and Its Components on Kerman University Students
Authors: Fariba Dortaj, Reza Asadinejad, Akram Dortaj, Atena Baziyar
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The aim of this study was to determine the effect of distance education (based on MOOC) on the components of academic engagement of Kerman PNU. The research was quasi-experimental method that cluster sampling with an appropriate volume was used in this study (one class in experimental group and one class in controlling group). Sampling method is single-stage cluster sampling. The statistical society is students of Kerman Payam Noor University, which) were selected 40 of them as sample (20 students in the control group and 20 students in experimental group). To test the hypothesis, it was used the analysis of univariate and Co-covariance to offset the initial difference (difference of control) in the experimental group and the control group. The instrument used in this study is academic engagement questionnaire of Zerang (2012) that contains component of cognitive, behavioral and motivational engagement. The results showed that there is no significant difference between mean scores of academic components of academic engagement in experimental group and the control group on the post-test, after elimination of the pre-test. The adjusted mean scores of components of academic engagement in the experimental group were higher than the adjusted average of scores after the test in the control group. The use of technology-based education in distance education has been effective in increasing cognitive engagement, motivational engagement and behavioral engagement among students. Experimental variable with the effect size 0.26, predicted 26% of cognitive engagement component variance. Experimental variable with the effect size 0.47, predicted 47% of the motivational engagement component variance. Experimental variable with the effect size 0.40, predicted 40% of behavioral engagement component variance. So teaching with technology (MOOC) has a positive impact on increasing academic engagement and academic performance of students in educational technology. The results suggest that technology (MOOC) is used to enrich the teaching of other lessons of PNU.Keywords: educational technology, distance education, components of academic engagement, mooc technology
Procedia PDF Downloads 14416662 Play in College: Shifting Perspectives and Creative Problem-Based Play
Authors: Agni Stylianou-Georgiou, Eliza Pitri
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This study is a design narrative that discusses researchers’ new learning based on changes made in pedagogies and learning opportunities in the context of a Cognitive Psychology and an Art History undergraduate course. The purpose of this study was to investigate how to encourage creative problem-based play in tertiary education engaging instructors and student-teachers in designing educational games. Course instructors modified content to encourage flexible thinking during game design problem-solving. Qualitative analyses of data sources indicated that Thinking Birds’ questions could encourage flexible thinking as instructors engaged in creative problem-based play. However, student-teachers demonstrated weakness in adopting flexible thinking during game design problem solving. Further studies of student-teachers’ shifting perspectives during different instructional design tasks would provide insights for developing the Thinking Birds’ questions as tools for creative problem solving.Keywords: creative problem-based play, educational games, flexible thinking, tertiary education
Procedia PDF Downloads 28616661 A Question of Ethics and Faith
Authors: Madhavi-Priya Singh, Liam Lowe, Farouk Arnaout, Ludmilla Pillay, Giordan Perez, Luke Mischker, Steve Costa
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An Emergency Department consultant identified the failure of medical students to complete the task of clerking a patient in its entirety. As six medical students on our first clinical placement, we recognised our own failure and endeavoured to examine why this failure was consistent among all medical students that had been given this task, despite our best motivations as adult learner. Our aim is to understand and investigate the elements which impeded our ability to learn and perform as medical students in the clinical environment, with reference to the prescribed task. We also aim to generate a discussion around the delivery of medical education with potential solutions to these barriers. Six medical students gathered together to have a comprehensive reflective discussion to identify possible factors leading to the failure of the task. First, we thoroughly analysed the delivery of the instructions with reference to the literature to identify potential flaws. We then examined personal, social, ethical, and cultural factors which may have impacted our ability to complete the task in its entirety. Through collation of our shared experiences, with support from discussion in the field of medical education and ethics, we identified two major areas that impacted our ability to complete the set task. First, we experienced an ethical conflict where we believed the inconvenience and potential harm inflicted on patients did not justify the positive impact the patient interaction would have on our medical learning. Second, we identified a lack of confidence stemming from multiple factors, including the conflict between preclinical and clinical learning, perceptions of perfectionism in the culture of medicine, and the influence of upward social comparison. After discussions, we found that the various factors we identified exacerbated the fears and doubts we already had about our own abilities and that of the medical education system. This doubt led us to avoid completing certain aspects of the tasks that were prescribed and further reinforced our vulnerability and perceived incompetence. Exploration of philosophical theories identified the importance of the role of doubt in education. We propose the need for further discussion around incorporating both pedagogic and andragogic teaching styles in clinical medical education and the acceptance of doubt as a driver of our learning. Doubt will continue to permeate our thoughts and actions no matter what. The moral or psychological distress that arises from this is the key motivating factor for our avoidance of tasks. If we accept this doubt and education embraces this doubt, it will no longer linger in the shadows as a negative and restrictive emotion but fuel a brighter dialogue and positive learning experience, ultimately assisting us in achieving our full potential.Keywords: medical education, clinical education, andragogy, pedagogy
Procedia PDF Downloads 12216660 The Effect Of Flights Schedules On Airline Choice Model For International Round-Trip Flights
Authors: Claudia Munoz, Henry Laniado
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In this research, the impact of outbound and return flight schedule preferences on airline choice for international trips is quantified. Several studies have used airline choice data to identify preferences and trade-offs of different air carrier service attributes, such as travel time, fare and frequencies. However, estimation of the effect return flight schedules have on airline choice for an international round-trip flight has not yet been studied in detail. The multinomial logit model found shows that airfare, travel time, arrival preference schedule in the outward journey, departure preference in the return journey and the schedule combination of round-trip flights are significantly affecting passenger choice behavior in international round-trip flights. it results indicated that return flight schedule preference plays a substantial role in air carrier choice and has a similar effect to outbound flight schedule preference. Thus, this study provides an analytical tool designed to provide a better understanding of international round-trip flight demand determinants and support carrier decisions.Keywords: flight schedule, airline choice, return flight, passenger choice behavior
Procedia PDF Downloads 616659 Effect of Building Construction Sizes on Project Delivery Methods in Nigeria
Authors: Nuruddeen Usman, Mohammad Sani
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The performance of project delivery methods has been an issue of concern to various stakeholders in the construction industry. The contracting system of project delivery is the traditional system used in the delivery of most public projects in Nigeria. The direct labor system is used most times as an alternative to the traditional system. There were so many complain about the performance of contracting system and the suitability of direct labor as an alternative to the delivery of public projects. Therefore, this paper is aimed at investigating the effect of project size on the project delivery methods in the completed public buildings. Questionnaires were self-administered to managerial staff in the study area and analyzed using descriptive statistics. The findings reveals that contracting system was choosing for large size building construction project delivery with higher frequency (F) of 40 (76.9%) against direct labor with 12 (23.1%). While the small size project, the result revealed a frequency (F) of 26 (50%) for contracting system and direct labor system respectively. Base on the research findings, the contracting system, was recommended for all sizes of building construction project delivery while direct labor system can only use as an alternative for small size building construction projects delivery.Keywords: construction size, contracting system, direct labour, effect
Procedia PDF Downloads 45016658 Performance Enrichment of Deep Feed Forward Neural Network and Deep Belief Neural Networks for Fault Detection of Automobile Gearbox Using Vibration Signal
Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan
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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal
Procedia PDF Downloads 10616657 The Effect of Manggong Bamboo Leaves Extract (Gigantochloa manggong) on Rat (Rattus novergicus) Blood Profile
Authors: Sri Rahayu, Supriyatin, Yuli Rahma Dini
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One of the consequences of excess physical activity is the oxidative stress which resulted in damage to blood cells. Oxidative stress condition can be reduced by an exogenous antioxidant. The natural exogenous antioxidant can be extracted from Manggong bamboo (Gigantochloa manggong). This research was aim to evaluate the effect of physical exercise and Manggong bamboo (Gigantochloa manggong) leaf extract on blood profile of rats. This research was conducted in July 2013 to May 2014 using experimental method with completely randomized design (CRD) with two factors, physical exercise and Manggong bamboo leaf extract. The rats blood profile to be measured were the level of erythrocyte cells, leucocyte cells and hemoglobin. Data were analyzed with parametric statistical 2-way ANOVA test (α = 0.05). Manggong bamboo leaf extract was non toxic and contained flavonoid, triterpenoid, saponin and alkaloid. There was an effect of physical exercise and manggong bamboo leaf extract on blood profile of rats. Data obtained on physical activity, giving erythrocyte cells (2.5 million/µl) and hemoglobin (12,42g/dL) declined compared to the number of leucocyte cells increases (6,500cells/L). Extract treatment was increased the erythrocytes (5,13 million/µl) and hemoglobin level (14,72 g/dL.) while the leukocytes level were decreased (1.591,67 cells/L). The extract and physical activity treatment showed an increase in erythrocytes (2,96 million/µl) and hemoglobin (14,3 g/dL) but decrease the number of leukocytes (1.291,67 cells/L). The conclusion was that physical activity and Manggong bamboo leafs extract gaves effect on the blood profile of white rat.Keywords: antioxidant, blood profile of rats, Manggong bamboo leaf extract, leukocytes
Procedia PDF Downloads 28116656 Organizational Commitment in Islamic Boarding School: The Implementation of Organizational Behavior Integrative Model
Authors: Siswoyo Haryono
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Purpose – The fundamental goal of this research is to see if the integrative organizational behavior model can be used effectively in Islamic boarding schools. This paper also seeks to assess the effect of Islamic organizational culture, leadership, and spiritual intelligence on teachers' organizational commitment to Islamic Boarding schools. The goal of the mediation analysis is to see if the Islamic work ethic has a more significant effect on the instructors' organizational commitment than the direct effects of Islamic organizational culture, leadership, and Islamic spiritual intelligence. Design/methodology/approach – A questionnaire survey was used to obtain data from teachers at Islamic Boarding Schools. This study used the AMOS technique for structural equation modeling to evaluate the expected direct effect. To test the hypothesized indirect effect, employed Sobel test. Findings – Islamic organizational culture, Islamic leadership, and Islamic spiritual intelligence significantly affect Islamic work ethic. When it comes to Islamic corporate culture, Islamic leadership, Islamic spiritual intelligence, and Islamic work ethics have a significant impact. The findings of the mediation study reveal that Islamic organizational culture, leadership, and spiritual intelligence influences organizational commitment through Islamic work ethic. The total effect analysis shows that the most effective path to increasing teachers’ organizational commitment is Islamic leadership - Islamic work ethic – organizational commitment. Originality/value – This study evaluates the Integrative Model of Organizational Behavior by Colquitt (2016) applied in Islamic Boarding School. The model consists of contemporary leadership and individual characteristic as the antecedent. The mediating variables of the model consist of individual mechanisms such as trust, justice, and ethic. Individual performance and organizational commitment are the model's outcomes. These variables, on the other hand, do not represent the Islamic viewpoint as a whole. As a result, this study aims to assess the role of Islamic principles in the model. The study employs reliability and validity tests to get reliable and valid measures. The findings revealed that the evaluation model is proven to improve organizational commitment at Islamic Boarding School.Keywords: Islamic leadership, Islamic spiritual intelligence, Islamic work ethic, organizational commitment, Islamic boarding school
Procedia PDF Downloads 15116655 Gas Lift Optimization Using Smart Gas Lift Valve
Authors: Mohamed A. G. H. Abdalsadig, Amir Nourian, G. G. Nasr, M. Babaie
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Gas lift is one of the most common forms of artificial lift, particularly for offshore wells because of its relative down hole simplicity, flexibility, reliability, and ability to operate over a large range of rates and occupy very little space at the well head. Presently, petroleum industry is investing in exploration and development fields in offshore locations where oil and gas wells are being drilled thousands of feet below the ocean in high pressure and temperature conditions. Therefore, gas-lifted oil wells are capable of failure through gas lift valves which are considered as the heart of the gas lift system for controlling the amount of the gas inside the tubing string. The gas injection rate through gas lift valve must be controlled to be sufficient to obtain and maintain critical flow, also, gas lift valves must be designed not only to allow gas passage through it and prevent oil passage, but also for gas injection into wells to be started and stopped when needed. In this paper, smart gas lift valve has been used to investigate the effect of the valve port size, depth of injection and vertical lift performance on well productivity; all these aspects have been investigated using PROSPER simulator program coupled with experimental data. The results show that by using smart gas lift valve, the gas injection rate can be controlled which leads to improved flow performance.Keywords: Effect of gas lift valve port size, effect water cut, vertical flow performance
Procedia PDF Downloads 28316654 Obtaining High Purity Hydroxyapatite from Bovine Bone: Effect of Chemical and Thermal Treatments
Authors: Hernandez Pardo Diego F., Guiza Arguello Viviana R., Coy Echeverria Ana, Viejo Abrante Fernando
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The biological hydroxyapatite obtained from bovine bone arouses great interest in its application as a material for bone regeneration due to its better bioactive behavior in comparison with synthetic hydroxyapatite. For this reason, the objective of the present investigation was to determine the effect of chemical and thermal treatments in obtaining biological bovine hydroxyapatite of high purity and crystallinity. Two different chemical reagents were evaluated (NaOH and HCl) with the aim to remove the organic matrix of the bovine cortical bone. On the other hand, for analyzing the effect of thermal treatment temperature was ranged between 500 and 1000°C for a holding time of 4 hours. To accomplish the above, the materials before and after the chemical and thermal treatments were characterized by elemental compositional analysis (CHN), infrared spectroscopy by Fourier transform (FTIR), RAMAN spectroscopy, scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and X-ray diffraction (XRD) and energy dispersion X-ray spectroscopy (EDS). The results allowed to establish that NaOH is more effective in the removal of the organic matrix of the bone when compared to HCl, whereas a thermal treatment at 700ºC for 4 hours was enough to obtain biological hydroxyapatite of high purity and crystallinity.Keywords: bovine bone, hydroxyapatite, biomaterials, thermal treatment
Procedia PDF Downloads 11116653 Effect of Varying Stocking Densities and Vitamin C (Ascorbic Acid) Supplementation on Growth Performance of Japanese Quails
Authors: T. S. Olugbemi, T. S. Friday, O. O. Olusola
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This experiment was carried out to assess the effect of different stocking densities and vitamin C supplementation on the performance of Japanese quails. Five hundred and twenty (520) unsexed quail birds of two (2) weeks of age were allotted randomly into nine (9) groups with 3 replicates each in a 3x3 factorial arrangement (3 stocking density levels and 3 graded vitamin C levels) with densities of 150, 120, 90 cm2/bird(11, 16, 21 birds). During the five weeks growing trial (2- 6 weeks), results showed that stocking density had significant effects on final weight (131.59g compared to 111.10g for the lowest), total and daily weight gain. No significance difference was observed for feed conversion ratio, age at first lay and first egg weight. Observations on haematological parameters (packed cell volume (PCV), total protein (TP), haemoglobin, red blood cell (RBC), lymphocyte, heterophil) on stocking density showed no significant differences. Vitamin C supplementation at 50mg/kg and 100mg/kg did not have any significant effect on the growth performance parameters of growing quails. Stocking density at 150cm2/bird had a better performance with or without vitamin C supplementation hence it is recommended that stocking rates of quails between the ages of 2 – 6 weeks should not be below 150cm2/bird.Keywords: anti-oxidants, performance, stress, stocking density
Procedia PDF Downloads 64016652 Value Added by Spirulina Platensis in Two Different Diets on Growth Performance, Gut Microbiota, and Meat Quality of Japanese Quails
Authors: Mohamed Yusuf
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Aim: The growth promoting the effect of the blue-green filamentous alga Spirulina platensis (SP) was observed on meat type Japanese quail with antibiotic growth promoter alternative and immune enhancing power. Materials and Methods: This study was conducted on 180 Japanese quail chicks for 4 weeks to find out the effect of diet type (vegetarian protein diet [VPD] and fish meal protein diet [FMPD])- Spirulina dose interaction (1 or 2 g/kg diet) on growth performance, gut microbiota, and sensory meat quality of growing Japanese quails (1-5 weeks old). Results: Data revealed improvement (p<0.05) of weight gain, feed conversion ratio, and European efficiency index due to 1, 2 g (SP)/kg VPD, and 2 g (SP)/kg FMPD, respectively. There was a significant decrease of ileum mean pH value by 1 g(SP)/kg VPD. Concerning gut microbiota, there was a trend toward an increase in Lactobacilli count in both 1; 2 g (SP)/kgVPD and 2 g (SP)/kg FMPD. It was concluded that 1 or 2 g (SP)/kg vegetarian diet may enhance parameters of performance without obvious effect on both meat quality and gut microbiota. Moreover, 1 and/or 2 g (SP) may not be invited to share fishmeal based diet for growing Japanese quails. Conclusion: Using of SP will support the profitable production of Japanese quails fed vegetable protein diet.Keywords: isocaloric, isonitrogenous, meat quality, performances, quails, spirulina, spirulina
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