Search results for: predicted mean vote
701 Estimation of Consolidating Settlement Based on a Time-Dependent Skin Friction Model Considering Column Surface Roughness
Authors: Jiang Zhenbo, Ishikura Ryohei, Yasufuku Noriyuki
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Improvement of soft clay deposits by the combination of surface stabilization and floating type cement-treated columns is one of the most popular techniques worldwide. On the basis of one dimensional consolidation model, a time-dependent skin friction model for the column-soil interaction is proposed. The nonlinear relationship between column shaft shear stresses and effective vertical pressure of the surrounding soil can be described in this model. The influence of column-soil surface roughness can be represented using a roughness coefficient R, which plays an important role in the design of column length. Based on the homogenization method, a part of floating type improved ground will be treated as an unimproved portion, which with a length of αH1 is defined as a time-dependent equivalent skin friction length. The compression settlement of this unimproved portion can be predicted only using the soft clay parameters. Apart from calculating the settlement of this composited ground, the load transfer mechanism is discussed utilizing model tests. The proposed model is validated by comparing with calculations and laboratory results of model and ring shear tests, which indicate the suitability and accuracy of the solutions in this paper.Keywords: floating type improved foundation, time-dependent skin friction, roughness, consolidation
Procedia PDF Downloads 468700 Design and Implementation of the Embedded Control System for the Electrical Motor Based Cargo Vehicle
Authors: Syed M. Rizvi, Yiqing Meng, Simon Iwnicki
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With an increased demand in the land cargo industry, it is predicted that the freight trade will rise to a record $1.1 trillion in revenue and volume in the following years to come. This increase is mainly driven by the e-commerce model ever so popular in the consumer market. Many innovative ideas have stemmed from this demand and change in lifestyle likes of which include e-bike cargo and drones. Rural and urban areas are facing air quality challenges to keep pollution levels in city centre to a minimum. For this purpose, this paper presents the design and implementation of a non-linear PID control system, employing a micro-controller and low cost sensing technique, for controlling an electrical motor based cargo vehicle with various loads, to follow a leading vehicle (bike). Within using this system, the cargo vehicle will have no load influence on the bike rider on different gradient conditions, such as hill climbing. The system is being integrated with a microcontroller to continuously measure several parameters such as relative displacement between bike and the cargo vehicle and gradient of the road, and process these measurements to create a portable controller capable of controlling the performance of electrical vehicle without the need of a PC. As a result, in the case of carrying 180kg of parcel weight, the cargo vehicle can maintain a reasonable spacing over a short length of sensor travel between the bike and itself.Keywords: cargo, e-bike, microcontroller, embedded system, nonlinear pid, self-adaptive, inertial measurement unit (IMU)
Procedia PDF Downloads 207699 Effectiveness of an Early Intensive Behavioral Intervention Program on Infants with Autism Spectrum Disorder
Authors: Dongjoo Chin
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The purpose of this study was to investigate the effectiveness of an Early Intensive Behavioral Intervention (EIBI) program on infants with autism spectrum disorder (ASD) and to explore the factors predicting the effectiveness of the program, focusing on the infant's age, language ability, problem behaviors, and parental stress. 19 pairs of infants aged between 2 and 5 years who have had been diagnosed with ASD, and their parents participated in an EIBI program at a clinic providing evidence-based treatment based on applied behavior analysis. The measurement tools which were administered before and after the EIBI program and compared, included PEP-R, a curriculum evaluation, K-SIB-R, K-Vineland-II, K-CBCL, and PedsQL for the infants, and included PSI-SF and BDI-II for the parents. Statistical analysis was performed using a sample t-test and multiple regression analysis and the results were as follows. The EIBI program showed significant improvements in overall developmental age, curriculum assessment, and quality of life for infants. There was no difference in parenting stress or depression. Furthermore, measures for both children and parents at the start of the program predicted neither PEP-R nor the degree of improvement in curriculum evaluation measured six months later at the end of the program. Based on these results, the authors suggest future directions for developing an effective intensive early intervention (EIBI) program for infants with ASD in Korea, and discuss the implications and limitations of this study.Keywords: applied behavior analysis, autism spectrum disorder, early intensive behavioral intervention, parental stress
Procedia PDF Downloads 173698 Reservoir Inflow Prediction for Pump Station Using Upstream Sewer Depth Data
Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim
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Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth
Procedia PDF Downloads 317697 Investigation of Mode II Fracture Toughness in Orthotropic Materials
Authors: Mahdi Fakoor, Nabi Mehri Khansari, Ahmadreza Farokhi
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Evaluation of mode II fracture toughness (KIIC) in composite materials is very hard problem to be solved, since it can be affected by many mechanisms of dissipation. Furthermore, non-linearity in its behavior can offer an extra difficulty to obtain accuracy in the results. Different reported values for KIIC in various references can prove the mentioned assertion. In this research, some solutions proposed based on the form of necessary corrections that should be executed on the common test fixtures. Due to the fact that the common test fixtures are not able to active toughening mechanisms in pure Mode II correctly, we have employed some structural modifications on common fixtures. Particularly, the Iosipescu test is used as start point. The tests are applied on graphite/epoxy; PMMA and Western White Pine Wood. Also, mixed mode I/II fracture limit curves are used to indicate the scattering in test results are really relevant to the creation of Fracture Process Zone (FPZ). In the present paper, shear load consideration applied at the predicted shear zone by considering some significant structural amendments that can active mode II toughening mechanisms. Indeed, the employed empirical method causes significant developing in repeatability and reproducibility as well. Moreover, a 3D Finite Element (FE) is performed for verification of the obtained results. Eventually, it is figured out that, a remarkable precision can be obtained in common test fixture in comparison with the previous one.Keywords: FPZ, shear test fixture, mode II fracture toughness, composite material, FEM
Procedia PDF Downloads 361696 Response Surface Methodology for the Optimization of Sugar Extraction from Phoenix dactylifera L.
Authors: Lila Boulekbache-Makhlouf, Kahina Djaoud, Myriam Tazarourte, Samir Hadjal, Khodir Madani
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In Algeria, important quantities of secondary date variety (Phoenix dactylifera L.) are generated in each campaign; their chemical composition is similar to that of commercial dates. The present work aims to valorize this common date variety (Degla-Beida) which is often poorly exploited. In this context, we tried to prepare syrup from the secondary date variety and to evaluate the effect of conventional extraction (CE) or water bath extraction (WBE) and alternative extraction (microwaves assisted extraction (MAE), and ultrasounds assisted extraction (UAE)) on its total sugar content (TSC), using response surface methodology (RSM). Then, the analysis of individual sugars was performed by high-performance liquid chromatography (HPLC). Maximum predicted TSC recoveries under the optimized conditions for MAE, UAE and CE were 233.248 ± 3.594 g/l, 202.889 ± 5.797 g/l, and 233.535 ± 5.412 g/l, respectively, which were close to the experimental values: 233.796 ± 1.898 g/l; 202.037 ± 3.401 g/l and 234.380 ± 2.425 g/l. HPLC analysis revealed high similarity in the sugar composition of date juices obtained by MAE (60.11% sucrose, 16.64% glucose and 23.25% fructose) and CE (50.78% sucrose, 20.67% glucose and 28.55% fructose), although a large difference was detected for that obtained by UAE (0.00% sucrose, 46.94% glucose and 53.06% fructose). Microwave-assisted extraction was the best method for the preparation of date syrup with an optimal recovery of total sugar content. However, ultrasound-assisted extraction was the best one for the preparation of date syrup with high content of reducing sugars.Keywords: dates, extraction, RSM, sugars, syrup
Procedia PDF Downloads 158695 Regenerative Agriculture: A Green Economy Tool for a Sustainable Crop Production
Authors: Meisam Zargar, Yurii Pleskachov, Mostafa Abdelkader, Aldaibe Ahmed, Maryam Bayat, Malek H. Walli, Shimendi Okbagabir
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The increased need of humankind for foodstuffs highlights the intensification of agricultural production. It is necessary either to increase the size of the sown area or to look for new approaches to improve agricultural land productivity. Developing new areas for cultivation is possible due to the intensification of soil cultivation. Nevertheless, this will decrease the effectiveness of de-carbonization programs since this approach will inevitably increase greenhouse gas emissions. Therefore, searching for new solutions to conserve natural resources while obtaining stable predicted crop yields is a vital scientific and technical task. For a long time, destructive land use methods have been used in crop production. The present stage of civilization's development and implementation of new techniques and methods of tillage and crops require the solution of technological, economic, and environmental problems simultaneously with the possibility of creating conditions for the regeneration of soil resources. Implementing these approaches became possible due to the development of new technology for the cultivation of crops based on the exact selective impact on the object of processing. This technology of particular effects of TIV combines the positive accumulated experience of traditional farming systems and resource-saving approaches. Particularly high-quality indicators and cost savings with introducing TIV can be achieved when used on row crops, including vegetables and melons.Keywords: agricultural machinery, vegetable, irrigation, strip system
Procedia PDF Downloads 29694 Optimization of Highly Oriented Pyrolytic Graphite Crystals for Neutron Optics
Authors: Hao Qu, Xiang Liu, Michael Crosby, Brian Kozak, Andreas K. Freund
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The outstanding performance of highly oriented pyrolytic graphite (HOPG) as an optical element for neutron beam conditioning is unequaled by any other crystalline material in the applications of monochromator, analyzer, and filter. This superiority stems from the favorable nuclear properties of carbon (small absorption and incoherent scattering cross-sections, big coherent scattering length) and the specific crystalline structure (small thermal diffuse scattering cross-section, layered crystal structure). The real crystal defect structure revealed by imaging techniques is correlated with the parameters used in the mosaic model (mosaic spread, mosaic block size, uniformity). The diffraction properties (rocking curve width as determined by both the intrinsic mosaic spread and the diffraction process, peak and integrated reflectivity, filter transmission) as a function of neutron wavelength or energy can be predicted with high accuracy and reliability by diffraction theory using empirical primary extinction coefficients extracted from a great amount of existing experimental data. The results of these calculations are given as graphs and tables permitting to optimize HOPG characteristics (mosaic spread, thickness, curvature) for any given experimental situation.Keywords: neutron optics, pyrolytic graphite, mosaic spread, neutron scattering, monochromator, analyzer
Procedia PDF Downloads 142693 Development of a General Purpose Computer Programme Based on Differential Evolution Algorithm: An Application towards Predicting Elastic Properties of Pavement
Authors: Sai Sankalp Vemavarapu
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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation
Procedia PDF Downloads 164692 Exploring Workaholism Determinants and Life Balance: A Mixed-Method Study Among Academic Nurse Educators
Authors: Ebtsam Aly Abou Hashish, Sharifah Abdulmuttalib Alsayed, Hend Abdu Alnajjar
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Background: Academic nurse educators play a crucial role in the educational environment, but the demands of their profession can lead to workaholism, which could result in an imbalance between work and personal life. Purpose: The study aimed to explore workaholism and life balance among academic nursing educators, as well as investigate the factors associated with workaholism. Methods: A mixed-methods design based on the ‘concurrent triangulation’ approach was employed. A convenience sample of 76 nurse educators completed the Dutch Work Addiction Scale (DUWAS) and the Life Balance Inventory (LBI), while a purposive sample of 20 nurse educators participated in semi-structured interviews. Inferential statistics and thematic analysis were used to analyze the data. Results: The researchers found a notable prevalence of workaholism among nurse educators, with 59.0 % reporting a mean score above 2.5 and 86.8 % perceiving an unbalanced life. Regression analysis indicated that workaholism negatively predicted life balance (B = 0.404, p < 0.001). The qualitative findings derived three themes as determinants of workaholism: antecedents, consequences, and personal and institutional strategies to mitigate workaholism among nursing educators. Conclusion: Educational institutions should develop comprehensive approaches to support and develop their academicians, fostering a positive work environment, work-life balance, employee well-being, and professional development.Keywords: workaholism, life balance, academic nurse educators, mixed-method
Procedia PDF Downloads 20691 Numerical Investigation of the Bio-fouling Roughness Effect on Tidal Turbine
Authors: O. Afshar
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Unlike other renewable energy sources, tidal current energy is an extremely reliable, predictable and continuous energy source as the current pattern and speed can be predicted throughout the year. A key concern associated with tidal turbines is their long-term reliability when operating in the hostile marine environment. Bio-fouling changes the physical shape and roughness of turbine components, hence altering the overall turbine performance. This paper seeks to employ Computational Fluid Dynamics (CFD) method to quantify the effects of this problem based on the obtained flow field information. The simulation is carried out on a NACA 63-618 aerofoil. The Reynolds Averaged Navier-Stokes (RANS) equations with Shear Stress Transport (SST) turbulent model are used to simulate the flow around the model. Different levels of fouling are studied on 2D aerofoil surface with quantified fouling height and density. In terms of lift and drag coefficient results, numerical results show good agreement with the experiment which was carried out in wind tunnel. Numerical results of research indicate that an increase in fouling thickness causes an increase in drag coefficient and a reduction in lift coefficient. Moreover, pressure gradient gradually becomes adverse as height of fouling increases. In addition, result by turbulent kinetic energy contour reveals it increases with fouling height and it extends into wake due to flow separation.Keywords: tidal energy, lift coefficient, drag coefficient, roughness
Procedia PDF Downloads 382690 A Comparative Analysis of Solid Waste Treatment Technologies on Cost and Environmental Basis
Authors: Nesli Aydin
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Waste management decision making in developing countries has moved towards being more pragmatic, transparent, sustainable and comprehensive. Turkey is required to make its waste related legislation compatible with European Legislation as it is a candidate country of the European Union. Improper Turkish practices such as open burning and open dumping practices must be abandoned urgently, and robust waste management systems have to be structured. The determination of an optimum waste management system in any region requires a comprehensive analysis in which many criteria are taken into account by stakeholders. In conducting this sort of analysis, there are two main criteria which are evaluated by waste management analysts; economic viability and environmentally friendliness. From an analytical point of view, a central characteristic of sustainable development is an economic-ecological integration. It is predicted that building a robust waste management system will need significant effort and cooperation between the stakeholders in developing countries such as Turkey. In this regard, this study aims to provide data regarding the cost and environmental burdens of waste treatment technologies such as an incinerator, an autoclave (with different capacities), a hydroclave and a microwave coupled with updated information on calculation methods, and a framework for comparing any proposed scenario performances on a cost and environmental basis.Keywords: decision making, economic viability, environmentally friendliness, waste management systems
Procedia PDF Downloads 305689 Characterization of Solanum tuberosum Ammonium Transporter Gene Using Bioinformatics Approach
Authors: Adewole Tomiwa Adetunji, Francis Bayo Lewu, Richard Mundembe
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Plants require nitrogen (N) to support desired production levels. There is a need for better understanding of N transport mechanism in order to improve N assimilation by plant root. Nitrogen is available to plants in the form of nitrate or ammonium, which are transported into the cell with the aid of various transport proteins. Ammonium transporters (AMTs) play a role in the uptake of ammonium, the form in which N is preferentially absorbed by plants. Solanum tuberosum AMT1 (StAMT1) was amplified, sequenced and characterized using molecular biology and bioinformatics methods. Nucleotide database sequences were used to design 976 base pairs AMT1-specific primers which include forward primer 5’- GCCATCGCCGCCGCCGG-3’ and reverse primer 5’-GGGTCAGATCCATACCCGC-3’. These primers were used to amplify the Solanum tuberosum AMT1 internal regions. Nucleotide sequencing, alignment and phylogenetic analysis assigned StAMT1 to the AMT1 family due to the clade and high similarity it shared with other plant AMT1 genes. The deduced amino acid sequences showed that StAMT1 is 92%, 83% and 76% similar to Solanum lycopersicum LeAMT1.1, Lotus japonicus LjAMT1.1, and Solanum lycopersicum LeAMT1.2 respectively. StAMT1 fragments were shown to correspond to the 5th-10th trans-membrane domains. Residue StAMT1 D15 is predicted to be essential for ammonium transport, while mutations of StAMT1 S76A may further enhance ammonium transport.Keywords: ammonium transporter, bioinformatics, nitrogen, primers, Solanum tuberosum
Procedia PDF Downloads 226688 A Mathematical Investigation of the Turkevich Organizer Theory in the Citrate Method for the Synthesis of Gold Nanoparticles
Authors: Emmanuel Agunloye, Asterios Gavriilidis, Luca Mazzei
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Gold nanoparticles are commonly synthesized by reducing chloroauric acid with sodium citrate. This method, referred to as the citrate method, can produce spherical gold nanoparticles (NPs) in the size range 10-150 nm. Gold NPs of this size are useful in many applications. However, the NPs are usually polydisperse and irreproducible. A better understanding of the synthesis mechanisms is thus required. This work thoroughly investigated the only model that describes the synthesis. This model combines mass and population balance equations, describing the NPs synthesis through a sequence of chemical reactions. Chloroauric acid reacts with sodium citrate to form aurous chloride and dicarboxy acetone. The latter organizes aurous chloride in a nucleation step and concurrently degrades into acetone. The unconsumed precursor then grows the formed nuclei. However, depending on the pH, both the precursor and the reducing agent react differently thus affecting the synthesis. In this work, we investigated the model for different conditions of pH, temperature and initial reactant concentrations. To solve the model, we used Parsival, a commercial numerical code, whilst to test it, we considered various conditions studied experimentally by different researchers, for which results are available in the literature. The model poorly predicted the experimental data. We believe that this is because the model does not account for the acid-base properties of both chloroauric acid and sodium citrate.Keywords: citrate method, gold nanoparticles, Parsival, population balance equations, Turkevich organizer theory
Procedia PDF Downloads 203687 Predicting Options Prices Using Machine Learning
Authors: Krishang Surapaneni
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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%Keywords: finance, linear regression model, machine learning model, neural network, stock price
Procedia PDF Downloads 75686 Predicting Dose Level and Length of Time for Radiation Exposure Using Gene Expression
Authors: Chao Sima, Shanaz Ghandhi, Sally A. Amundson, Michael L. Bittner, David J. Brenner
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In a large-scale radiologic emergency, potentially affected population need to be triaged efficiently using various biomarkers where personal dosimeters are not likely worn by the individuals. It has long been established that radiation injury can be estimated effectively using panels of genetic biomarkers. Furthermore, the rate of radiation, in addition to dose of radiation, plays a major role in determining biological responses. Therefore, a better and more accurate triage involves estimating both the dose level of the exposure and the length of time of that exposure. To that end, a large in vivo study was carried out on mice with internal emitter caesium-137 (¹³⁷Cs). Four different injection doses of ¹³⁷Cs were used: 157.5 μCi, 191 μCi, 214.5μCi, and 259 μCi. Cohorts of 6~7 mice from the control arm and each of the dose levels were sacrificed, and blood was collected 2, 3, 5, 7 and 14 days after injection for microarray RNA gene expression analysis. Using a generalized linear model with penalized maximum likelihood, a panel of 244 genes was established and both the doses of injection and the number of days after injection were accurately predicted for all 155 subjects using this panel. This has proven that microarray gene expression can be used effectively in radiation biodosimetry in predicting both the dose levels and the length of exposure time, which provides a more holistic view on radiation exposure and helps improving radiation damage assessment and treatment.Keywords: caesium-137, gene expression microarray, multivariate responses prediction, radiation biodosimetry
Procedia PDF Downloads 198685 Predicting the Quality of Life on the Basis of Perceived Social Support among Patients with Coronary Artery Bypass Graft
Authors: Azadeh Yaraghchi, Reza Bagherian Sararoodi, Niknaz Salehi Moghadam, Mohammad Hossein Mandegar, Adis Kraskian Mujembari, Omid Rezaei
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Background: Quality of life is one of the most important consequences of disease in psychosomatic disorders. Many psychological factors are considered in predicting quality of life in patients with coronary artery bypass graft (CABG). The present study was aimed to determine the relationship between perceived social support and quality of life in patients with coronary artery bypass graft (CABG). Methods: The population included 82 patients who had undergone CABG from October 2014 to May 2015 in four different hospitals in Tehran. The patients were evaluated with Multi-dimension scale of perceived social support (MSPSS) and after three months follow up were evaluated by Short-Form quality of life questionnaire (SF-36). The obtained data were analyzed through Pearson correlation test and multiple variable regression models. Findings: A relationship between perceived social support and quality of life in patients with CABG was observed (r=0.374, p<0.01). The results showed that 22.4% of variation in quality of life is predicted by perceived social support components (p<0.01, R2 =0.224). Conclusion: Based on the results, perceived social support is one of the predictors of quality of life in patients with coronary artery bypass graft. Accordingly, these results can be useful in conceiving proactive policies, detecting high risk patients and planning for psychological interventions.Keywords: coronary artery bypass graft, perceived social support, psychological factors, quality of life
Procedia PDF Downloads 369684 Modeling and Experimental Verification of Crystal Growth Kinetics in Glass Forming Alloys
Authors: Peter K. Galenko, Stefanie Koch, Markus Rettenmayr, Robert Wonneberger, Evgeny V. Kharanzhevskiy, Maria Zamoryanskaya, Vladimir Ankudinov
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We analyze the structure of undercooled melts, crystal growth kinetics and amorphous/crystalline microstructure of rapidly solidifying glass-forming Pd-based and CuZr-based alloys. A dendrite growth model is developed using a combination of the kinetic phase-field model and mesoscopic sharp interface model. The model predicts features of crystallization kinetics in alloys from thermodynamically controlled growth (governed by the Gibbs free energy change on solidification) to the kinetically limited regime (governed by atomic attachment-detachment processes at the solid/liquid interface). Comparing critical undercoolings observed in the crystallization kinetics with experimental data on melt viscosity, atomistic simulation's data on liquid microstructure and theoretically predicted dendrite growth velocity allows us to conclude that the dendrite growth kinetics strongly depends on the cluster structure changes of the melt. The obtained data of theoretical and experimental investigations are used for interpretation of microstructure of samples processed in electro-magnetic levitator on board International Space Station in the frame of the project "MULTIPHAS" (European Space Agency and German Aerospace Center, 50WM1941) and "KINETIKA" (ROSKOSMOS).Keywords: dendrite, kinetics, model, solidification
Procedia PDF Downloads 120683 Artificial Neural Network to Predict the Optimum Performance of Air Conditioners under Environmental Conditions in Saudi Arabia
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
Procedia PDF Downloads 74682 The Link between Childhood Maltreatment and Psychological Distress: The Mediation and Moderation Roles of Cognitive Distortion, Alexithymia, and Eudemonic Well-Being
Authors: Siqi Fang, Man Cheung Chung
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This study examined the inter-relationship between childhood maltreatment, cognitive distortion, alexithymia, eudemonic well-being, and psychological distress. One hundred and eighty-two university students participated in the study and completed an online survey comprising the Childhood Trauma Questionnaire, Cognitive Distortion Scale, Toronto Alexithymia Scale, Psychological Well-Being Scale, and General Health Questionnaire-28. Hierarchical multiple regression analysis showed that child maltreatment, perceptions of hopelessness and helplessness, preoccupation with danger, personal growth, and purpose in life predicted psychological distress. However, alexithymia was not a significant predictor. Further analysis using the regression models with bootstrapping procedure showed that feeling hopeless, helpless and preoccupation with danger mediated the path between child maltreatment and psychological distress. Meanwhile, coping with beliefs in personal growth and life purpose moderated the mediation effects of distorted cognition on psychological distress. To conclude, childhood maltreatment is associated with psychological distress. This relationship is influenced by people’s perceptions of life being hopeless, helpless or dangerous. At the same time, the effect of hopelessness, helplessness, and feelings of danger also depends on the degree of using coping strategies of positive psychological functioning.Keywords: alexithymia, childhood maltreatment, cognitive distortion, eudemonic well-being, psychological distress
Procedia PDF Downloads 344681 An Advanced Exponential Model for Seismic Isolators Having Hardening or Softening Behavior at Large Displacements
Authors: Nicolò Vaiana, Giorgio Serino
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In this paper, an advanced Nonlinear Exponential Model (NEM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement in the relatively large displacements range and a hardening or softening behavior at large displacements, is presented. The mathematical model is validated by comparing the experimental force-displacement hysteresis loops obtained during cyclic tests, conducted on a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted analytically. Good agreement between the experimental and simulated results shows that the proposed model can be an effective numerical tool to predict the force-displacement relationship of seismic isolation devices within the large displacements range. Compared to the widely used Bouc-Wen model, unable to simulate the response of seismic isolators at large displacements, the proposed one allows to avoid the numerical solution of a first order nonlinear ordinary differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort. Furthermore, the proposed model can simulate the smooth transition of the hysteresis loops from small to large displacements by adopting only one set of five parameters determined from the experimental hysteresis loops having the largest amplitude.Keywords: base isolation, hardening behavior, nonlinear exponential model, seismic isolators, softening behavior
Procedia PDF Downloads 329680 Determinants of Poverty: A Logit Regression Analysis of Zakat Applicants
Authors: Zunaidah Ab Hasan, Azhana Othman, Abd Halim Mohd Noor, Nor Shahrina Mohd Rafien
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Zakat is a portion of wealth contributed from financially able Muslims to be distributed to predetermine recipients; main among them are the poor and the needy. Distribution of the zakat fund is given with the objective to lift the recipients from poverty. Due to the multidimensional and multifaceted nature of poverty, it is imperative that the causes of poverty are properly identified for assistance given by zakat authorities reached the intended target. Despite, various studies undertaken to identify the poor correctly, there are reports of the poor not receiving the adequate assistance required from zakat. Thus, this study examines the determinants of poverty among applicants for zakat assistance distributed by the State Islamic Religious Council in Malacca (SIRCM). Malacca is a state in Malaysia. The respondents were based on the list of names of new zakat applicants for the month of April and May 2014 provided by SIRCM. A binary logistic regression was estimated based on this data with either zakat applications is rejected or accepted as the dependent variable and set of demographic variables and health as the explanatory variables. Overall, the logistic model successfully predicted factors of acceptance of zakat applications. Three independent variables namely gender, age; size of households and health significantly explain the likelihood of a successful zakat application. Among others, the finding suggests the importance of focusing on providing education opportunity in helping the poor.Keywords: logistic regression, zakat distribution, status of zakat applications, poverty, education
Procedia PDF Downloads 336679 Modeling Stream Flow with Prediction Uncertainty by Using SWAT Hydrologic and RBNN Neural Network Models for Agricultural Watershed in India
Authors: Ajai Singh
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Simulation of hydrological processes at the watershed outlet through modelling approach is essential for proper planning and implementation of appropriate soil conservation measures in Damodar Barakar catchment, Hazaribagh, India where soil erosion is a dominant problem. This study quantifies the parametric uncertainty involved in simulation of stream flow using Soil and Water Assessment Tool (SWAT), a watershed scale model and Radial Basis Neural Network (RBNN), an artificial neural network model. Both the models were calibrated and validated based on measured stream flow and quantification of the uncertainty in SWAT model output was assessed using ‘‘Sequential Uncertainty Fitting Algorithm’’ (SUFI-2). Though both the model predicted satisfactorily, but RBNN model performed better than SWAT with R2 and NSE values of 0.92 and 0.92 during training, and 0.71 and 0.70 during validation period, respectively. Comparison of the results of the two models also indicates a wider prediction interval for the results of the SWAT model. The values of P-factor related to each model shows that the percentage of observed stream flow values bracketed by the 95PPU in the RBNN model as 91% is higher than the P-factor in SWAT as 87%. In other words the RBNN model estimates the stream flow values more accurately and with less uncertainty. It could be stated that RBNN model based on simple input could be used for estimation of monthly stream flow, missing data, and testing the accuracy and performance of other models.Keywords: SWAT, RBNN, SUFI 2, bootstrap technique, stream flow, simulation
Procedia PDF Downloads 370678 Chatter Prediction of Curved Thin-walled Parts Considering Variation of Dynamic Characteristics Based on Acoustic Signals Acquisition
Authors: Damous Mohamed, Zeroudi Nasredine
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High-speed milling of thin-walled parts with complex curvilinear profiles often encounters machining instability, commonly referred to as chatter. This phenomenon arises due to the dynamic interaction between the cutting tool and the part, exacerbated by the part's low rigidity and varying dynamic characteristics along the tool path. This research presents a dynamic model specifically developed to predict machining stability for such curved thin-walled components. The model employs the semi-discretization method, segmenting the tool trajectory into small, straight elements to locally approximate the behavior of an inclined plane. Dynamic characteristics for each segment are extracted through experimental modal analysis and incorporated into the simulation model to generate global stability lobe diagrams. Validation of the model is conducted through cutting tests where acoustic intensity is measured to detect instabilities. The experimental data align closely with the predicted stability limits, confirming the model's accuracy and effectiveness. This work provides a comprehensive approach to enhancing machining stability predictions, thereby improving the efficiency and quality of high-speed milling operations for thin-walled parts.Keywords: chatter, curved thin-walled part, semi-discretization method, stability lobe diagrams
Procedia PDF Downloads 26677 Comparison of Leeway Space Predictions Using Moyers and Tanaka-Johnston Upper Jaw and Lower Jaw on Batak Tribe Between Male and Female in Elementary School Students in Medan City, Sumatera Utara, Indonesia: A Cross-sectional Study
Authors: Hilda Fitria Lubis, Erna Sulistyawati
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Objective: The study aims to compare Leeway space averages between Moyers and Tanaka-Johnston's analysis of elementary school students from the Batak tribe in Medan City. Material and Methods: The study involved 106 students from the Batak tribe elementary school in Medan, comprising 53 male and 53 female students. The samples obtained were then printed on both jaws to obtain a working model, and the mesiodistal width of the four permanent biting teeth of the lower jaw and the amount of space available on the canine-premolar region, as well as the predicted mesiodistal number of the canine-premolar on the Moyers probability table with a 75% degree of confidence and the Tanaka-Johnston formula. Results: Using Moyers analysis, students at Batak Elementary School in Medan City have an average Leeway space value of 2 mm on the upper jaw and 2.78 mm on the lower jaw. The average Leeway spatial value using Tanaka-Johnston analysis in the Batak tribe in elementary school in Medan City is 1.33 mm on the top jaw and 2.39 mm on the bottom jaw. Conclusion: According to Moyers and Tanaka-Johnsnton's analysis of both the upper and lower jaws in elementary school students of the Batak tribe in Medan City, there is a significant difference between Leeway's average space.Keywords: leeways space, batak tribe, genders, diagnosis
Procedia PDF Downloads 31676 Stress Hyperglycemia: A Predictor of Major Adverse Cardiac Events in Non-Diabetic Patients With Acute Heart Failure
Authors: Fahad Raj Khan, Suleman Khan
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There is a lack of consensus about the predictive value of raised blood glucose levels in terms of major adverse cardiac events (MACEs) in non-diabetic patients admitted for acute decompensated heart failure. The purpose of this research was to examine the long-term prognosis of acute decompensated heart failure (ADHF) in non-diabetic persons who had increased blood glucose levels, i.e., stress hyperglycemia, at the time of their ADHF hospitalization. The research involved 650 non-diabetic patients. Based on their admission stress hyperglycemia, they were divided into two groups.ie with and without (SHGL). The two groups' one-year outcomes for major adverse cardiac events (MACEs) were compared, and key predictors of MACEs were discovered. For statistical analysis, the two-tailed Mann-Whitney U test, Fisher's exact test, and binary logistic regression analysis were utilized. SHGL was found in 353 (54.3%) individuals. It was more frequent in men than in women. About 27% of patients with SHGL had previously been admitted for ADHF. Almost 62% were hypertensive, whereas 14 % had CKD. MACEs were significantly predicted by SHGL, HTN, prior hospitalization for ADHF, CKD, and cardiogenic shock upon admission. SHGL at the time of ADHF admission, independent of DM status, may be a predictive indication of MACEs.Keywords: stress hyperglycemia, acute heart failure, major adverse cardiac events, MACEs
Procedia PDF Downloads 94675 The Influence of Masculinity and Femininity on Lucid Dreaming and Psychosis Proneness
Authors: Anum Atiq, Haya Fatimah
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Lucid dream is a dream where one is aware that one is dreaming, and they also might be able to influence their dreaming states. Logically, since lucidity cues towards high awareness, it should be negatively associated with proneness to psychosis. However, this association is scarcely studied. Furthermore, although gender differences and similarities in psychopathology have been thoroughly studied, there is room for research in the influence of masculinity and femininity, regardless of one’s sex, on proneness to psychosis. The aim of this study is twofold: 1) We investigated if dream lucidity was negatively associated with psychosis proneness; and 2) We explored the influence of masculinity and femininity on psychosis proneness, over and above the sex. Data were collected by convenience sampling from the undergraduate students enrolled at the University of Management and Technology, Lahore. The sample consisted of 53 students among the age range of 18-26 (men=24, women=29). Masculinity and femininity were measured using the masculinity and femininity subscales of the Personality Attributes Questionnaire. Dream lucidity was measured with The Lucidity and Consciousness in Dreams Scale; and the reality testing sub scale of The Inventory of Personality Organization was used to measure proneness to psychosis. Pearson correlation analysis revealed that psychosis proneness was significantly and negatively correlated with dream lucidity-insight and negative emotion in dreams, but not with other aspects of dream lucidity. Furthermore, masculinity, in both men and women, was positively related with lucid dreaming, and negatively with psychosis proneness. Following this, linear regression analysis showed that psychosis proneness was negatively predicted by masculinity even after controlling for gender. Lucid dreamer and masculinity both have characteristic of independence, emotional control and internal locus of control. Therefore, masculinity makes lucid dreaming less risk of psychosis in both genders.Keywords: lucid dreaming, psychosis, gender, masculinity and femininity
Procedia PDF Downloads 216674 Increasing of Gain in Unstable Thin Disk Resonator
Authors: M. Asl. Dehghan, M. H. Daemi, S. Radmard, S. H. Nabavi
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Thin disk lasers are engineered for efficient thermal cooling and exhibit superior performance for this task. However the disk thickness and large pumped area make the use of this gain format in a resonator difficult when constructing a single-mode laser. Choosing an unstable resonator design is beneficial for this purpose. On the other hand, the low gain medium restricts the application of unstable resonators to low magnifications and therefore to a poor beam quality. A promising idea to enable the application of unstable resonators to wide aperture, low gain lasers is to couple a fraction of the out coupled radiation back into the resonator. The output coupling gets dependent on the ratio of the back reflection and can be adjusted independently from the magnification. The excitation of the converging wave can be done by the use of an external reflector. The resonator performance is numerically predicted. First of all the threshold condition of linear, V and 2V shape resonator is investigated. Results show that the maximum magnification is 1.066 that is very low for high quality purposes. Inserting an additional reflector covers the low gain. The reflectivity and the related magnification of a 350 micron Yb:YAG disk are calculated. The theoretical model was based on the coupled Kirchhoff integrals and solved numerically by the Fox and Li algorithm. Results show that with back reflection mechanism in combination with increasing the number of beam incidents on disk, high gain and high magnification can occur.Keywords: unstable resonators, thin disk lasers, gain, external reflector
Procedia PDF Downloads 412673 Finite Element Analysis of Raft Foundation on Various Soil Types under Earthquake Loading
Authors: Qassun S. Mohammed Shafiqu, Murtadha A. Abdulrasool
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The design of shallow foundations to withstand different dynamic loads has given considerable attention in recent years. Dynamic loads may be due to the earthquakes, pile driving, blasting, water waves, and machine vibrations. But, predicting the behavior of shallow foundations during earthquakes remains a difficult task for geotechnical engineers. A database for dynamic and static parameters for different soils in seismic active zones in Iraq is prepared which has been collected from geophysical and geotechnical investigation works. Then, analysis of a typical 3-D soil-raft foundation system under earthquake loading is carried out using the database. And a parametric study has been carried out taking into consideration the influence of some parameters on the dynamic behavior of the raft foundation, such as raft stiffness, damping ratio as well as the influence of the earthquake acceleration-time records. The results of the parametric study show that the settlement caused by the earthquake can be decreased by about 72% with increasing the thickness from 0.5 m to 1.5 m. But, it has been noticed that reduction in the maximum bending moment by about 82% was predicted by decreasing the raft thickness from 1.5 m to 0.5 m in all sites model. Also, it has been observed that the maximum lateral displacement, the maximum vertical settlement and the maximum bending moment for damping ratio 0% is about 14%, 20%, and 18% higher than that for damping ratio 7.5%, respectively for all sites model.Keywords: shallow foundation, seismic behavior, raft thickness, damping ratio
Procedia PDF Downloads 148672 Collision Tumor of Plasmacytoma with Hematological and Non-Hematological Malignancies
Authors: Arati Inamdar, Siddharth Bhattacharyya, Kester Haye
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Collision tumors are rare entities characterized by neoplasms of two different cell populations with distinct separating boundaries. Such tumors could be benign, malignant, or a combination of both. The exact mechanism of origin for collision tumors is predicted to be tumor heterogeneity or concurrent occurrence of neoplasm in the same organ. We present two cases of plasmacytoma presenting as a collision tumor, one with a tumor of hematological origin and another with a non-hematological origin, namely Chronic Lymphocytic Leukemia and Adenocarcinoma of the colon, respectively. The immunohistochemical stains and flowcytometry analysis performed on the specimens aided incorrect diagnosis. Interestingly, neoplastic cells of plasmacytoma in the first case demonstrated strong cytokeratin along with weak Epithelial Specific Antigen/ Epithelial cell adhesion molecule Monoclonal Antibody (MOC31) positivity, indicating that the tumor may influence the microenvironment of the tumor in the vicinity. Furthermore, the next-generation sequencing studies performed on the specimen with plasmacytoma and chronic lymphocytic lymphoma demonstrated BReast CAncer gene (BRCA2) and Tumor Necrosis Factor Alpha Induced Protein 3 (TNFAIP3) as a disease associated variants suggestive of risk for multiple tumors including collision tumors. Our reports highlight the unique collision tumors involving plasmacytoma, which have never been reported previously, as well as provide necessary insights about the underline genetic aberrations and tumor heterogeneity through sequencing studies and allow clonality assessment for subsequent tumors.Keywords: BRCA2, collision tumor, chronic lymphocytic leukemia, plasmacytoma
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