Search results for: background noise statistical modeling
10864 Photo-Fenton Decolorization of Methylene Blue Adsolubilized on Co2+ -Embedded Alumina Surface: Comparison of Process Modeling through Response Surface Methodology and Artificial Neural Network
Authors: Prateeksha Mahamallik, Anjali Pal
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In the present study, Co(II)-adsolubilized surfactant modified alumina (SMA) was prepared, and methylene blue (MB) degradation was carried out on Co-SMA surface by visible light photo-Fenton process. The entire reaction proceeded on solid surface as MB was embedded on Co-SMA surface. The reaction followed zero order kinetics. Response surface methodology (RSM) and artificial neural network (ANN) were used for modeling the decolorization of MB by photo-Fenton process as a function of dose of Co-SMA (10, 20 and 30 g/L), initial concentration of MB (10, 20 and 30 mg/L), concentration of H2O2 (174.4, 348.8 and 523.2 mM) and reaction time (30, 45 and 60 min). The prediction capabilities of both the methodologies (RSM and ANN) were compared on the basis of correlation coefficient (R2), root mean square error (RMSE), standard error of prediction (SEP), relative percent deviation (RPD). Due to lower value of RMSE (1.27), SEP (2.06) and RPD (1.17) and higher value of R2 (0.9966), ANN was proved to be more accurate than RSM in order to predict decolorization efficiency.Keywords: adsolubilization, artificial neural network, methylene blue, photo-fenton process, response surface methodology
Procedia PDF Downloads 26010863 Modeling of Transformer Winding for Transients: Frequency-Dependent Proximity and Skin Analysis
Authors: Yazid Alkraimeen
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Precise prediction of dielectric stresses and high voltages of power transformers require the accurate calculation of frequency-dependent parameters. A lack of accuracy can result in severe damages to transformer windings. Transient conditions is stuided by digital computers, which require the implementation of accurate models. This paper analyzes the computation of frequency-dependent skin and proximity losses included in the transformer winding model, using analytical equations and Finite Element Method (FEM). A modified formula to calculate the proximity and the skin losses is presented. The results of the frequency-dependent parameter calculations are verified using the Finite Element Method. The time-domain transient voltages are obtained using Numerical Inverse Laplace Transform. The results show that the classical formula for proximity losses is overestimating the transient voltages when compared with the results obtained from the modified method on a simple transformer geometry.Keywords: fast front transients, proximity losses, transformer winding modeling, skin losses
Procedia PDF Downloads 14110862 Risk Spillover Between Stock Indices and Real Estate Mixed Copula Modeling
Authors: Hina Munir Abbasi
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The current paper examines the relationship and diversification ability of Islamic stock indices /conventional stocks indices and Real Estate Investment Trust (REITs).To represent conditional dependency between stocks and REITs in a more realistic way, new modeling technique, time-varying copula with switching dependence is used. It represents reliance structure more accurately and realistically than a single copula regime as dependence may alter between positive and negative correlation regimes with time. The fluctuating behavior of markets has significant impact on economic variables; especially the downward trend during crisis. Overall addition of Real Estate Investment Trust in stocks portfolio reduces risks and provide better diversification benefit. Results varied depending upon the circumstances of the country. REITs provides better diversification benefits for Islamic Stocks, when both markets are bearish and can provide hedging benefit for conventional stocks portfolio.Keywords: conventional stocks, real estate investment trust, copula, diversification, risk spillover, safe heaven
Procedia PDF Downloads 8910861 A Joint Possibilistic-Probabilistic Tool for Load Flow Uncertainty Assessment-Part I: Formulation
Authors: Morteza Aien, Masoud Rashidinejad, Mahmud Fotuhi-Firuzabad
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As energetic and environmental issues are getting more and more attention all around the world, the penetration of distributed energy resources (DERs) mainly those harvesting renewable energies (REs) ascends with an unprecedented rate. This matter causes more uncertainties to appear in the power system context; ergo, the uncertainty analysis of the system performance is an obligation. The uncertainties of any system can be represented probabilistically or possibilistically. Since sufficient historical data about all the system variables is not available, therefore, they do not have a probability density function (PDF) and must be represented possibilistiacally. When some of system uncertain variables are probabilistic and some are possibilistic, neither the conventional pure probabilistic nor pure possibilistic methods can be implemented. Hence, a combined solution is appealed. The first of this two-paper series formulates a new possibilistic-probabilistic tool for the load flow uncertainty assessment. The proposed methodology is based on the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. This possibilistic- probabilistic formulation is solved in the second companion paper in an uncertain load flow (ULF) study problem.Keywords: probabilistic uncertainty modeling, possibilistic uncertainty modeling, uncertain load flow, wind turbine generator
Procedia PDF Downloads 56610860 Computational Fluid Dynamics Modeling of Physical Mass Transfer of CO₂ by N₂O Analogy Using One Fluid Formulation in OpenFOAM
Authors: Phanindra Prasad Thummala, Umran Tezcan Un, Ahmet Ozan Celik
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Removal of CO₂ by MEA (monoethanolamine) in structured packing columns depends highly on the gas-liquid interfacial area and film thickness (liquid load). CFD (computational fluid dynamics) is used to find the interfacial area, film thickness and their impact on mass transfer in gas-liquid flow effectively in any column geometry. In general modeling approaches used in CFD derive mass transfer parameters from standard correlations based on penetration or surface renewal theories. In order to avoid the effect of assumptions involved in deriving the correlations and model the mass transfer based solely on fluid properties, state of art approaches like one fluid formulation is useful. In this work, the one fluid formulation was implemented and evaluated for modeling the physical mass transfer of CO₂ by N₂O analogy in OpenFOAM CFD software. N₂O analogy avoids the effect of chemical reactions on absorption and allows studying the amount of CO₂ physical mass transfer possible in a given geometry. The computational domain in the current study was a flat plate with gas and liquid flowing in the countercurrent direction. The effect of operating parameters such as flow rate, the concentration of MEA and angle of inclination on the physical mass transfer is studied in detail. Liquid side mass transfer coefficients obtained by simulations are compared to the correlations available in the literature and it was found that the one fluid formulation was effectively capturing the effects of interface surface instabilities on mass transfer coefficient with higher accuracy. The high mesh refinement near the interface region was found as a limiting reason for utilizing this approach on large-scale simulations. Overall, the one fluid formulation is found more promising for CFD studies involving the CO₂ mass transfer.Keywords: one fluid formulation, CO₂ absorption, liquid mass transfer coefficient, OpenFOAM, N₂O analogy
Procedia PDF Downloads 22410859 Parental Expectations and Student Performance in Secondary School Mathematics Education
Authors: Daya Weerasinghe
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Parental expectations often differ to that of their children and the influence and involvement of parents, at home, may affect the student performance in the classroom. This paper presents results from a survey of Asian and European background secondary school mathematics students (N=128) in Melbourne, Australia. Student responses to survey questions were analysed using confirmatory factor analysis, followed by t-tests and ANOVA. The aim of the analysis was to identify similarities and differences in parental expectations in relation to ethnicity, gender, and the year level of the students. The notable findings from the analysis showed no significant difference (at 0.05 level) in parental expectations and student performance, in relation to ethnicity or gender. Conversely, there was a significant difference in both parental expectations and student performance between year 7 and year 12 students. Further, whilst there was a significant difference in parental expectations between year 7 and year 11 students, the students’ performances were not significantly different. The results suggest further research may be needed to understand the parental expectations and student performance between the lower and upper secondary school mathematics students.Keywords: ethnic background, gender, parental expectations, student performance, year level
Procedia PDF Downloads 31610858 Overweight and Neurocognitive Functioning: Unraveling the Antagonistic Relationship in Adolescents
Authors: Swati Bajpai, S. P. K Jena
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Background: There is dramatic increase in the prevalence and severity of overweight in adolescents, raising concerns about their psychosocial and cognitive consequences, thereby indicating the immediate need to understand the effects of increased weight on scholastic performance. Although the body of research is currently limited, available results have identified an inverse relationship between obesity and cognition in adolescents. Aim: to examine the association between increased Body Mass Index in adolescents and their neurocognitive functioning. Methods: A case –control study of 28 subjects in the age group of 11-17 years (14 Males and 14 females) was taken on the basis of main inclusion criteria (Body Mass Index). All of them were randomized to (experimental group: overweight) and (control group: normal weighted). A complete neurocognitive assessment was carried out using validated psychological scales namely, Color Progressive Matrices (to assess intelligence); Bender Visual Motor Gestalt Test (Perceptual motor functioning); PGI-Memory Scale for Children (memory functioning) and Malin’s Intelligence Scale Indian Children (verbal and performance ability). Results: statistical analysis of the results depicted that 57% of the experimental group lack in cognitive abilities, especially in general knowledge (99.1±12.0 vs. 102.8±6.7), working memory (91.5±8.4 vs. 93.1±8.7), concrete ability (82.3±11.5 vs. 92.6±1.7) and perceptual motor functioning (1.5±1.0 vs. 0.3±0.9) as compared to control group. Conclusion: Our investigations suggest that weight gain results, at least in part, from a neurological predisposition characterized by reduced executive function, and in turn obesity itself has a compounding negative impact on the brain. Though, larger sample is needed to make more affirmative claims.Keywords: adolescents, body mass index, neurocognition, obesity
Procedia PDF Downloads 48910857 Knowledge, Attitude and Practice of Pregnant Women toward Antenatal Care at Public Hospitals in Sana'a City-Yemen
Authors: Abdulfatah Al-Jaradi, Marzoq Ali Odhah, Abdulnasser A. Haza’a
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Background: Antenatal care can be defined as the care provided by skilled healthcare professionals to pregnant women and adolescent girls to ensure the best health conditions for both mother and baby during pregnancy. The components of ANC include risk identification; prevention and management of pregnancy-related or concurrent diseases; and health education and health promotion. The aim of this study: to assess the knowledge, attitude, and practice of pregnant women regarding antenatal care. Methodology: A descriptive KAP study was conducting in public hospitals in Sana'a City-Yemen. The study population was included all pregnant women that intended to the prenatal department and clinical outpatient department, the final sample size was 371 pregnant women, a self-administered questionnaire was used to collect the data, statistical package for social sciences SPSS was used to data analysis. The results: Most (79%) of pregnant women were had correct answers in total knowledge regarding antenatal care, and about two-thirds (67%) of pregnant women were had performance practice regarding antenatal care and two-third (68%) of pregnant women were had a positive attitude. Conclusions & Recommendations: We concluded that a significant association between overall knowledge and practice level toward antenatal care and demographic characteristics of pregnant women, women (residence place, level of education, did your husband support you in attending antenatal care and place of delivery of the last baby), at (P-value ≤ 0.05). We recommended more education and training courses, lecturers and education sessions in clinical facilitators focused ANC, which relies on evidence-based interventions provided to women during pregnancy by skilled healthcare providers such as midwives, doctors, and nurses.Keywords: antenatal care, knowledge, practice, attitude, pregnant women
Procedia PDF Downloads 19910856 An Application of Sinc Function to Approximate Quadrature Integrals in Generalized Linear Mixed Models
Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif
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This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function
Procedia PDF Downloads 39710855 Mapping of Urban Green Spaces Towards a Balanced Planning in a Coastal Landscape
Authors: Rania Ajmi, Faiza Allouche Khebour, Aude Nuscia Taibi, Sirine Essasi
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Urban green spaces (UGS) as an important contributor can be a significant part of sustainable development. A spatial method was employed to assess and map the spatial distribution of UGS in five districts in Sousse, Tunisia. Ecological management of UGS is an essential factor for the sustainable development of the city; hence the municipality of Sousse has decided to support the districts according to different green spaces characters. And to implement this policy, (1) a new GIS web application was developed, (2) then the implementation of the various green spaces was carried out, (3) a spatial mapping of UGS using Quantum GIS was realized, and (4) finally a data processing and statistical analysis with RStudio programming language was executed. The intersection of the results of the spatial and statistical analyzes highlighted the presence of an imbalance in terms of the spatial UGS distribution in the study area. The discontinuity between the coast and the city's green spaces was not designed in a spirit of network and connection, hence the lack of a greenway that connects these spaces to the city. Finally, this GIS support will be used to assess and monitor green spaces in the city of Sousse by decision-makers and will contribute to improve the well-being of the local population.Keywords: distributions, GIS, green space, imbalance, spatial analysis
Procedia PDF Downloads 21110854 Diagnostic and Prognostic Use of Kinetics of Microrna and Cardiac Biomarker in Acute Myocardial Infarction
Authors: V. Kuzhandai Velu, R. Ramesh
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Background and objectives: Acute myocardial infarction (AMI) is the most common cause of mortality and morbidity. Over the last decade, microRNAs (miRs) have emerged as a potential marker for detecting AMI. The current study evaluates the kinetics and importance of miRs in the differential diagnosis of ST-segment elevated MI (STEMI) and non-STEMI (NSTEMI) and its correlation to conventional biomarkers and to predict the immediate outcome of AMI for arrhythmias and left ventricular (LV) dysfunction. Materials and Method: A total of 100 AMI patients were recruited for the study. Routine cardiac biomarker and miRNA levels were measured during diagnosis and serially at admission, 6, 12, 24, and 72hrs. The baseline biochemical parameters were analyzed. The expression of miRs was compared between STEMI and NSTEMI at different time intervals. Diagnostic utility of miR-1, miR-133, miR-208, and miR-499 levels were analyzed by using RT-PCR and with various diagnostics statistical tools like ROC, odds ratio, and likelihood ratio. Results: The miR-1, miR-133, and miR-499 showed peak concentration at 6 hours, whereas miR-208 showed high significant differences at all time intervals. miR-133 demonstrated the maximum area under the curve at different time intervals in the differential diagnosis of STEMI and NSTEMI which was followed by miR-499 and miR-208. Evaluation of miRs for predicting arrhythmia and LV dysfunction using admission sample demonstrated that miR-1 (OR = 8.64; LR = 1.76) and miR-208 (OR = 26.25; LR = 5.96) showed maximum odds ratio and likelihood respectively. Conclusion: Circulating miRNA showed a highly significant difference between STEMI and NSTEMI in AMI patients. The peak was much earlier than the conventional biomarkers. miR-133, miR-208, and miR-499 can be used in the differential diagnosis of STEMI and NSTEMI, whereas miR-1 and miR-208 could be used in the prediction of arrhythmia and LV dysfunction, respectively.Keywords: myocardial infarction, cardiac biomarkers, microRNA, arrhythmia, left ventricular dysfunction
Procedia PDF Downloads 13210853 Improvement of Central Composite Design in Modeling and Optimization of Simulation Experiments
Authors: A. Nuchitprasittichai, N. Lerdritsirikoon, T. Khamsing
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Simulation modeling can be used to solve real world problems. It provides an understanding of a complex system. To develop a simplified model of process simulation, a suitable experimental design is required to be able to capture surface characteristics. This paper presents the experimental design and algorithm used to model the process simulation for optimization problem. The CO2 liquefaction based on external refrigeration with two refrigeration circuits was used as a simulation case study. Latin Hypercube Sampling (LHS) was purposed to combine with existing Central Composite Design (CCD) samples to improve the performance of CCD in generating the second order model of the system. The second order model was then used as the objective function of the optimization problem. The results showed that adding LHS samples to CCD samples can help capture surface curvature characteristics. Suitable number of LHS sample points should be considered in order to get an accurate nonlinear model with minimum number of simulation experiments.Keywords: central composite design, CO2 liquefaction, latin hypercube sampling, simulation-based optimization
Procedia PDF Downloads 17010852 Re-identification Risk and Mitigation in Federated Learning: Human Activity Recognition Use Case
Authors: Besma Khalfoun
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In many current Human Activity Recognition (HAR) applications, users' data is frequently shared and centrally stored by third parties, posing a significant privacy risk. This practice makes these entities attractive targets for extracting sensitive information about users, including their identity, health status, and location, thereby directly violating users' privacy. To tackle the issue of centralized data storage, a relatively recent paradigm known as federated learning has emerged. In this approach, users' raw data remains on their smartphones, where they train the HAR model locally. However, users still share updates of their local models originating from raw data. These updates are vulnerable to several attacks designed to extract sensitive information, such as determining whether a data sample is used in the training process, recovering the training data with inversion attacks, or inferring a specific attribute or property from the training data. In this paper, we first introduce PUR-Attack, a parameter-based user re-identification attack developed for HAR applications within a federated learning setting. It involves associating anonymous model updates (i.e., local models' weights or parameters) with the originating user's identity using background knowledge. PUR-Attack relies on a simple yet effective machine learning classifier and produces promising results. Specifically, we have found that by considering the weights of a given layer in a HAR model, we can uniquely re-identify users with an attack success rate of almost 100%. This result holds when considering a small attack training set and various data splitting strategies in the HAR model training. Thus, it is crucial to investigate protection methods to mitigate this privacy threat. Along this path, we propose SAFER, a privacy-preserving mechanism based on adaptive local differential privacy. Before sharing the model updates with the FL server, SAFER adds the optimal noise based on the re-identification risk assessment. Our approach can achieve a promising tradeoff between privacy, in terms of reducing re-identification risk, and utility, in terms of maintaining acceptable accuracy for the HAR model.Keywords: federated learning, privacy risk assessment, re-identification risk, privacy preserving mechanisms, local differential privacy, human activity recognition
Procedia PDF Downloads 1710851 Heat Transfer Modeling of 'Carabao' Mango (Mangifera indica L.) during Postharvest Hot Water Treatments
Authors: Hazel James P. Agngarayngay, Arnold R. Elepaño
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Mango is the third most important export fruit in the Philippines. Despite the expanding mango trade in world market, problems on postharvest losses caused by pests and diseases are still prevalent. Many disease control and pest disinfestation methods have been studied and adopted. Heat treatment is necessary to eliminate pests and diseases to be able to pass the quarantine requirements of importing countries. During heat treatments, temperature and time are critical because fruits can easily be damaged by over-exposure to heat. Modeling the process enables researchers and engineers to study the behaviour of temperature distribution within the fruit over time. Understanding physical processes through modeling and simulation also saves time and resources because of reduced experimentation. This research aimed to simulate the heat transfer mechanism and predict the temperature distribution in ‘Carabao' mangoes during hot water treatment (HWT) and extended hot water treatment (EHWT). The simulation was performed in ANSYS CFD Software, using ANSYS CFX Solver. The simulation process involved model creation, mesh generation, defining the physics of the model, solving the problem, and visualizing the results. Boundary conditions consisted of the convective heat transfer coefficient and a constant free stream temperature. The three-dimensional energy equation for transient conditions was numerically solved to obtain heat flux and transient temperature values. The solver utilized finite volume method of discretization. To validate the simulation, actual data were obtained through experiment. The goodness of fit was evaluated using mean temperature difference (MTD). Also, t-test was used to detect significant differences between the data sets. Results showed that the simulations were able to estimate temperatures accurately with MTD of 0.50 and 0.69 °C for the HWT and EHWT, respectively. This indicates good agreement between the simulated and actual temperature values. The data included in the analysis were taken at different locations of probe punctures within the fruit. Moreover, t-tests showed no significant differences between the two data sets. Maximum heat fluxes obtained at the beginning of the treatments were 394.15 and 262.77 J.s-1 for HWT and EHWT, respectively. These values decreased abruptly at the first 10 seconds and gradual decrease was observed thereafter. Data on heat flux is necessary in the design of heaters. If underestimated, the heating component of a certain machine will not be able to provide enough heat required by certain operations. Otherwise, over-estimation will result in wasting of energy and resources. This study demonstrated that the simulation was able to estimate temperatures accurately. Thus, it can be used to evaluate the influence of various treatment conditions on the temperature-time history in mangoes. When combined with information on insect mortality and quality degradation kinetics, it could predict the efficacy of a particular treatment and guide appropriate selection of treatment conditions. The effect of various parameters on heat transfer rates, such as the boundary and initial conditions as well as the thermal properties of the material, can be systematically studied without performing experiments. Furthermore, the use of ANSYS software in modeling and simulation can be explored in modeling various systems and processes.Keywords: heat transfer, heat treatment, mango, modeling and simulation
Procedia PDF Downloads 25010850 A Comparison of Caesarean Section Indications and Characteristics in 2009 and 2020 in a Saudi Tertiary Hospital
Authors: Sarah K. Basudan, Ragad I. Al Jazzar, Zeinah Sulaihim, Hanan M. Al-Kadri
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Background: Cesarean section has been increasing in recent years, with a wide range of etiologies contributing to this rise. This study aimed to assess the indications, outcomes, and complications in Riyadh, Saudi Arabia. Methods: A Retrospective Cohort study was conducted at King Abdulaziz medical city. The study includes two cohorts: G1 (2009) and G2 (2020) groups who met the inclusion criteria. The data was transferred to the SPSS (statistical package for social sciences) version 24 for analysis. The initial descriptive statistics were run for all variables, including numerical and categorical data. The numerical data were reported as median, and standard deviation and categorical data were reported as frequencies and percentages. Results: The data were collected from 399 women who were divided into two groups, G1(199) and G2(200). The mean age of all participants is 32+-6; G1 and G2 had significant differences in age means with 30+-6 and 34+-5, respectively, with a p-value of <0.001, which indicates delayed fertility by four years. Moreover, a breech presentation was less likely to occur in G2 (OR 0.64, CI: 0.21-0.62. P<0.001). Nonetheless, maternal causes such as repeated C-sections and maternal medical conditions were more likely to happen in G2 (OR 1.5, CI: 1.04-2.38, p=0.03) and (OR 5.4, CI: 1.12-23.9, P=0.01), respectively. Furthermore, postpartum hemorrhage showed an increase of 12% in G2 (OR 5.4, CI: 2.2-13.4, p<0.001). G2 was more likely to be admitted to the neonatal intensive care unit (NICU) (OR 16, CI: 7.4-38.7) and to special care baby (SCB) (OR 7.2, CI: 3.9-13.1), both with a p-value<0.001 compared to regular nursery admission. Conclusion: There are multiple factors that are contributing to the increase in c section rate in a Saudi tertiary hospitals. The factors were suggested to be previous c-sections, abnormal fetal heart rate, malpresentation, and maternal or fetal medical conditions.Keywords: cesarean sections, maternal indications, maternal complications, neonatal condition
Procedia PDF Downloads 9510849 Generation of High-Quality Synthetic CT Images from Cone Beam CT Images Using A.I. Based Generative Networks
Authors: Heeba A. Gurku
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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.Keywords: CT images, CBCT images, cycle GAN, AGGAN
Procedia PDF Downloads 8710848 A Comparative Analysis of Geometric and Exponential Laws in Modelling the Distribution of the Duration of Daily Precipitation
Authors: Mounia El Hafyani, Khalid El Himdi
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Precipitation is one of the key variables in water resource planning. The importance of modeling wet and dry durations is a crucial pointer in engineering hydrology. The objective of this study is to model and analyze the distribution of wet and dry durations. For this purpose, the daily rainfall data from 1967 to 2017 of the Moroccan city of Kenitra’s station are used. Three models are implemented for the distribution of wet and dry durations, namely the first-order Markov chain, the second-order Markov chain, and the truncated negative binomial law. The adherence of the data to the proposed models is evaluated using Chi-square and Kolmogorov-Smirnov tests. The Akaike information criterion is applied to assess the most effective model distribution. We go further and study the law of the number of wet and dry days among k consecutive days. The calculation of this law is done through an algorithm that we have implemented based on conditional laws. We complete our work by comparing the observed moments of the numbers of wet/dry days among k consecutive days to the calculated moment of the three estimated models. The study shows the effectiveness of our approach in modeling wet and dry durations of daily precipitation.Keywords: Markov chain, rainfall, truncated negative binomial law, wet and dry durations
Procedia PDF Downloads 13010847 Iterative Reconstruction Techniques as a Dose Reduction Tool in Pediatric Computed Tomography Imaging: A Phantom Study
Authors: Ajit Brindhaban
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Background and Purpose: Computed Tomography (CT) scans have become the largest source of radiation in radiological imaging. The purpose of this study was to compare the quality of pediatric Computed Tomography (CT) images reconstructed using Filtered Back Projection (FBP) with images reconstructed using different strengths of Iterative Reconstruction (IR) technique, and to perform a feasibility study to assess the use of IR techniques as a dose reduction tool. Materials and Methods: An anthropomorphic phantom representing a 5-year old child was scanned, in two stages, using a Siemens Somatom CT unit. In stage one, scans of the head, chest and abdomen were performed using standard protocols recommended by the scanner manufacturer. Images were reconstructed using FBP and 5 different strengths of IR. Contrast-to-Noise Ratios (CNR) were calculated from average CT number and its standard deviation measured in regions of interest created in the lungs, bone, and soft tissues regions of the phantom. Paired t-test and the one-way ANOVA were used to compare the CNR from FBP images with IR images, at p = 0.05 level. The lowest strength value of IR that produced the highest CNR was identified. In the second stage, scans of the head was performed with decreased mA(s) values relative to the increase in CNR compared to the standard FBP protocol. CNR values were compared in this stage using Paired t-test at p = 0.05 level. Results: Images reconstructed using IR technique had higher CNR values (p < 0.01.) in all regions compared to the FBP images, at all strengths of IR. The CNR increased with increasing IR strength of up to 3, in the head and chest images. Increases beyond this strength were insignificant. In abdomen images, CNR continued to increase up to strength 5. The results also indicated that, IR techniques improve CNR by a up to factor of 1.5. Based on the CNR values at strength 3 of IR images and CNR values of FBP images, a reduction in mA(s) of about 20% was identified. The images of the head acquired at 20% reduced mA(s) and reconstructed using IR at strength 3, had similar CNR as FBP images at standard mA(s). In the head scans of the phantom used in this study, it was demonstrated that similar CNR can be achieved even when the mA(s) is reduced by about 20% if IR technique with strength of 3 is used for reconstruction. Conclusions: The IR technique produced better image quality at all strengths of IR in comparison to FBP. IR technique can provide approximately 20% dose reduction in pediatric head CT while maintaining the same image quality as FBP technique.Keywords: filtered back projection, image quality, iterative reconstruction, pediatric computed tomography imaging
Procedia PDF Downloads 15210846 Effects of a Student-Centered Approach to Assessment on Students' Attitudes towards 'Applied Statistics' Course
Authors: Anduela Lile
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The purpose of this cross sectional study was to investigate the effectiveness of teaching and learning Statistics from a student centered perspective in higher education institutions. Statistics education has emphasized the application of tangible and interesting examples in order to motivate students learning about statistical concepts. Participants in this study were 112 bachelor students enrolled in the ‘Applied Statistics’ course in Sports University of Tirana. Experimental group students received a student-centered teaching approach; Control group students received an instructor-centered teaching approach. This study found student-centered approach student group had statistically significantly higher assessments scores (52.1 ± 18.9) at the end of the evaluation compared to instructor-centered approach student group (61.8 ± 16.4), (t (108) = 2.848, p = 0.005). Results concluded that student-centered perspective can improve student positive attitude to statistical methods and to motivate project work. Therefore, findings of this study may be very useful to the higher education institutions to establish their learning strategies especially for courses related to Statistics.Keywords: student-centered, instructor-centered, course assessment, learning outcomes, applied statistics
Procedia PDF Downloads 28510845 Planning of Construction Material Flow Using Hybrid Simulation Modeling
Authors: A. M. Naraghi, V. Gonzalez, M. O'Sullivan, C. G. Walker, M. Poshdar, F. Ying, M. Abdelmegid
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Discrete Event Simulation (DES) and Agent Based Simulation (ABS) are two simulation approaches that have been proposed to support decision-making in the construction industry. Despite the wide use of these simulation approaches in the construction field, their applications for production and material planning is still limited. This is largely due to the dynamic and complex nature of construction material supply chain systems. Moreover, managing the flow of construction material is not well integrated with site logistics in traditional construction planning methods. This paper presents a hybrid of DES and ABS to simulate on-site and off-site material supply processes. DES is applied to determine the best production scenarios with information of on-site production systems, while ABS is used to optimize the supply chain network. A case study of a construction piling project in New Zealand is presented illustrating the potential benefits of using the proposed hybrid simulation model in construction material flow planning. The hybrid model presented can be used to evaluate the impact of different decisions on construction supply chain management.Keywords: construction supply-chain management, simulation modeling, decision-support tools, hybrid simulation
Procedia PDF Downloads 21010844 The Impact of Group Hope Therapy on the Life Satisfaction, Happiness, and Hopefulness of Older Adults
Authors: Gholamzadeh Sakineh, Jedi Maryam, Fereshteh Dehghanrad
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Background: Mental and psychological issues are common among older adults. Positive psychology theorists and researchers recommend focusing on constructs such as happiness, life satisfaction and hope rather than dwelling on negative experiences and perceptions. Objective: The research aim was to evaluate the impact of hope therapy interventions on the life satisfaction, happiness, and hopefulness of older adults in Iran. Methodology: This study used a quasi-experimental design. A convenience sample of 32 older adults was recruited from a retirement center in Shiraz, Iran. Participants were randomly assigned to either a control group (n = 16) or an experimental group (n = 16). The experimental group received eight sessions of hope therapy, each lasting 1.5 hours. The data for this study were collected using Snyder's Adult Hope Scale (AHS), Oxford Happiness Questionnaire, and Life Satisfaction Index-Z. The questionnaires were administered before, immediately after the intervention, and two months later. Descriptive and analytical statistical tests were used to analyze the data using SPSS version 19. Descriptive statistics were used to describe the sample characteristics and the distribution of the data. Analytical statistics were used to test the research hypotheses. Findings: The results showed that the hope therapy intervention significantly increased the life satisfaction and hopefulness of older adults (p < 0.05). In addition, the influence of time was also significant (p < 0.05). However, the intervention did not affect happiness in statistically significant ways. Conclusions: The findings of this study support the theoretical importance of hope therapy in improving the life satisfaction and hopefulness of older adults. Hope therapy interventions can be considered as an effective way to improve the emotional well-being and quality of life of older adults.Keywords: older adults, life satisfaction, happiness, hopefulness, hope therapy
Procedia PDF Downloads 8610843 Seroprevalence and Associated Factors of Hepatitis B and Hepatitis C Viral Infections among Prisoners in Tigrai, Northern Ethiopia
Authors: Belaynesh Tsegay Beyene, Teklay Gebrecherkos, Atsebaha Gebrekidan Kahsay, Mahmud Abdulkader
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Background: Hepatitis B and C viruses are of important health and socioeconomic problem of the globe with remarkable diseases and deaths in Sub-Saharan African countries. The burden of hepatitis is unknown in the prison settings of Tigrai. Therefore, we aimed to describe the seroprevalence and associated factors of hepatitis B and C viruses among prisoners of Tigrai, Ethiopia. Methods: A cross-sectional study was carried out from February 2020 to May 2020 at the prison facilities of Tigrai. Demographics and associated factors were collected from 315 prisoners prospectively. Five milliliter of blood was collected and tested using rapid tests kits of HBsAg (Zhejiang orient Gene Biotech Co., Ltd., China) and HCV antibodies (Volkan Kozmetik Sanayi Ve Ticaret Ltd. STI, Turkey). Positive samples were confirmed using enzyme-linked immunosorbent assay (ELISA) (Beijing Wantai Biological Pharmacy Enterprise Co. Ltd). Data were analyzed using Statistical Package for Social Sciences (SPSS) version 20 and p < 0.05 was considered statistically significant. Results: The overall seroprevalence of HBV and HCV were 25 (7.9%) and 1(0.3%), respectively. The majority of hepatitis B viral infections were identified from the age groups of 18-25 years (10.7%) and unmarried prisoners (11.8%). Prisoners greater than 100 per cell [AOR =3.95, 95% CI= (1.15, 13.6, p =0.029)] and having history of alcohol consumption [AOR =3.01, 95% CI= (1.17, 7.74, p =0.022)] were significantly associated with HBV infections. Conclusions: The seroprevalence of HBV among prisoners was nearly high or borderline (7.9%) with a very low HCV prevalence (0.3%). HBV was most prevalent among young adults, large number of prisoners per cell and those who had history of alcohol consumption. This study recommends that there should be prison-focused intervention including regular health education by emphasis on the mode of transmission and introducing HBV screening policy for prisoners especially when they enter to the prison.Keywords: seroprevalence, HBV, HCV, prisoners, Tigrai
Procedia PDF Downloads 8010842 Application of Artificial Neural Network and Background Subtraction for Determining Body Mass Index (BMI) in Android Devices Using Bluetooth
Authors: Neil Erick Q. Madariaga, Noel B. Linsangan
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Body Mass Index (BMI) is one of the different ways to monitor the health of a person. It is based on the height and weight of the person. This study aims to compute for the BMI using an Android tablet by obtaining the height of the person by using a camera and measuring the weight of the person by using a weighing scale or load cell. The height of the person was estimated by applying background subtraction to the image captured and applying different processes such as getting the vanishing point and applying Artificial Neural Network. The weight was measured by using Wheatstone bridge load cell configuration and sending the value to the computer by using Gizduino microcontroller and Bluetooth technology after the amplification using AD620 instrumentation amplifier. The application will process the images and read the measured values and show the BMI of the person. The study met all the objectives needed and further studies will be needed to improve the design project.Keywords: body mass index, artificial neural network, vanishing point, bluetooth, wheatstone bridge load cell
Procedia PDF Downloads 32810841 Diabetes Mellitus and Blood Glucose Variability Increases the 30-day Readmission Rate after Kidney Transplantation
Authors: Harini Chakkera
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Background: Inpatient hyperglycemia is an established independent risk factor among several patient cohorts with hospital readmission. This has not been studied after kidney transplantation. Nearly one-third of patients who have undergone a kidney transplant reportedly experience 30-day readmission. Methods: Data on first-time solitary kidney transplantations were retrieved between September 2015 to December 2018. Information was linked to the electronic health record to determine a diagnosis of diabetes mellitus and extract glucometeric and insulin therapy data. Univariate logistic regression analysis and the XGBoost algorithm were used to predict 30-day readmission. We report the average performance of the models on the testing set on five bootstrapped partitions of the data to ensure statistical significance. Results: The cohort included 1036 patients who received kidney transplantation, and 224 (22%) experienced 30-day readmission. The machine learning algorithm was able to predict 30-day readmission with an average AUC of 77.3% (95% CI 75.30-79.3%). We observed statistically significant differences in the presence of pretransplant diabetes, inpatient-hyperglycemia, inpatient-hypoglycemia, and minimum and maximum glucose values among those with higher 30-day readmission rates. The XGBoost model identified the index admission length of stay, presence of hyper- and hypoglycemia and recipient and donor BMI values as the most predictive risk factors of 30-day readmission. Additionally, significant variations in the therapeutic management of blood glucose by providers were observed. Conclusions: Suboptimal glucose metrics during hospitalization after kidney transplantation is associated with an increased risk for 30-day hospital readmission. Optimizing the hospital blood glucose management, a modifiable factor, after kidney transplantation may reduce the risk of 30-day readmission.Keywords: kidney, transplant, diabetes, insulin
Procedia PDF Downloads 9610840 Characterization of Climatic Drought in the Saiss Plateau (Morocco) Using Statistical Indices
Authors: Abdeghani Qadem
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Climate change is now an undeniable reality with increasing impacts on water systems worldwide, especially leading to severe drought episodes. The Southern Mediterranean region is particularly affected by this drought, which can have devastating consequences on water resources. Morocco, due to its geographical location in North Africa and the Southern Mediterranean, is especially vulnerable to these effects of climate change, particularly drought. In this context, this article focuses on the study of climate variability and drought characteristics in the Saiss Plateau region and its adjacent areas with the Middle Atlas, using specific statistical indices. The study begins by analyzing the annual precipitation variation, with a particular emphasis on data homogenization and gap filling using a regional vector. Then, the analysis delves into drought episodes in the region, using the Standardized Precipitation Index (SPI) over a 12-month period. The central objective is to accurately assess significant drought changes between 1980 and 2015, based on data collected from nine meteorological stations located in the study area.Keywords: climate variability, regional vector, drought, standardized precipitation index, Saiss Plateau, middle atlas
Procedia PDF Downloads 7410839 Numerical Study of Off-Design Performance of a Highly Loaded Low Pressure Turbine Cascade
Authors: Shidvash Vakilipour, Mehdi Habibnia, Rouzbeh Riazi, Masoud Mohammadi, Mohammad H. Sabour
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The flow field passing through a highly loaded low pressure (LP) turbine cascade is numerically investigated at design and off-design conditions. The Field Operation And Manipulation (OpenFOAM) platform is used as the computational Fluid Dynamics (CFD) tool. Firstly, the influences of grid resolution on the results of k-ε, k-ω, and LES turbulence models are investigated and compared with those of experimental measurements. A numerical pressure under-shoot is appeared near the end of blade pressure surface which is sensitive to grid resolution and flow turbulence modeling. The LES model is able to resolve separation on a coarse and fine grid resolutions. Secondly, the off-design flow condition is modeled by negative and positive inflow incidence angles. The numerical experiments show that a separation bubble generated on blade pressure side is predicted by LES. The total pressure drop is also been calculated at incidence angle between -20◦ and +8◦. The minimum total pressure drop is obtained by k-ω and LES at the design point.Keywords: low pressure turbine, off-design performance, openFOAM, turbulence modeling, flow separation
Procedia PDF Downloads 36610838 Lack of BIM Training: Investigating Practical Solutions for the State of Kuwait
Authors: Noor M. Abdulfattah, Ahmed M. Khalafallah, Nabil A. Kartam
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Despite the evident benefits of building information modeling (BIM) to the construction industry, it faces significant implementation challenges in the State of Kuwait. This study investigates the awareness of construction stakeholders of BIM implementation challenges, and identifies various solutions to overcome these challenges. Specifically, the main objectives of this study are to: (1) characterize the barriers that deter utilization of BIM, (2) examine the awareness of engineers, architects, and construction stakeholders of these barriers, and (3) identify practical solutions to facilitate BIM utilization. A questionnaire survey was designed to collect data on the aforementioned objectives from local companies and senior BIM experts. It was found that engineers are highly aware of BIM implementation barriers. In addition, it was concluded from the questionnaire that the biggest barrier is the lack of BIM training. Based on expert feedback, the study concluded with a number of recommendations on how to overcome the barriers of BIM utilization. This should prove useful to the construction industry stakeholders and can lead to significant changes to design and construction practices.Keywords: building information modeling (BIM), construction, information technology, challenges
Procedia PDF Downloads 26510837 Impact of Instagram Food Bloggers on Consumer (Generation Z) Decision Making Process in Islamabad. Pakistan
Authors: Tabinda Sadiq, Tehmina Ashfaq Qazi, Hoor Shumail
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Recently, the advent of emerging technology has created an emerging generation of restaurant marketing. It explores the aspects that influence customers’ decision-making process in selecting a restaurant after reading food bloggers' reviews online. The motivation behind this research is to investigate the correlation between the credibility of the source and their attitude toward restaurant visits. The researcher collected the data by distributing a survey questionnaire through google forms by employing the Source credibility theory. Non- probability purposive sampling technique was used to collect data. The questionnaire used a predeveloped and validated scale by Ohanian to measure the relationship. Also, the researcher collected data from 250 respondents in order to investigate the influence of food bloggers on Gen Z's decision-making process. SPSS statistical version 26 was used for statistical testing and analyzing the data. The findings of the survey revealed that there is a moderate positive correlation between the variables. So, it can be analyzed that food bloggers do have an impact on Generation Z's decision making process.Keywords: credibility, decision making, food bloggers, generation z, e-wom
Procedia PDF Downloads 7810836 Review and Analysis of Parkinson's Tremor Genesis Using Mathematical Model
Authors: Pawan Kumar Gupta, Sumana Ghosh
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Parkinson's Disease (PD) is a long-term neurodegenerative movement disorder of the central nervous system with vast symptoms related to the motor system. The common symptoms of PD are tremor, rigidity, bradykinesia/akinesia, and postural instability, but the clinical symptom includes other motor and non‐motor issues. The motor symptoms of the disease are consequence of death of the neurons in a region of the midbrain known as substantia nigra pars compacta, leading to decreased level of a neurotransmitter known as dopamine. The cause of this neuron death is not clearly known but involves formation of Lewy bodies, an abnormal aggregation or clumping of the protein alpha-synuclein in the neurons. Unfortunately, there is no cure for PD, and the management of this disease is challenging. Therefore, it is critical for a patient to be diagnosed at early stages. A limited choice of drugs is available to improve the symptoms, but those become less and less effective over time. Apart from that, with rapid growth in the field of science and technology, other methods such as multi-area brain stimulation are used to treat patients. In order to develop advanced techniques and to support drug development for treating PD patients, an accurate mathematical model is needed to explain the underlying relationship of dopamine secretion in the brain with the hand tremors. There has been a lot of effort in the past few decades on modeling PD tremors and treatment effects from a computational point of view. These models can effectively save time as well as the cost of drug development for the pharmaceutical industry and be helpful for selecting appropriate treatment mechanisms among all possible options. In this review paper, an effort is made to investigate studies on PD modeling and analysis and to highlight some of the key advances in the field over the past centuries with discussion on the current challenges.Keywords: Parkinson's disease, deep brain stimulation, tremor, modeling
Procedia PDF Downloads 14210835 Nonlinear Finite Element Modeling of Reinforced Concrete Flat Plate-Inclined Column Connection
Authors: Rabab Allouzi, Amer Alkloub
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As the complex shaped buildings become a popular trend for architects, this paper is presented to investigate the performance of reinforced concrete flat plate-inclined column connection. The studies on the inclined column and flat plate connections are not sufficient in comparison to those on the conventional structures. The effect of column angle of inclination on the punching shear strength is found significant and studied herein. This paper presents a non-linear finite element based modeling approach to estimate behavior of RC flat plate inclined column connection. Results from simulations of RC flat plate-straight column connection show good agreement with experimental response of specimens tested by other researchers. The model is further used to study the response of inclined columns to punching at various ranges of inclination angles. The inclination angle can be included in the punching shear strength provisions provided by ACI 318-14 to account for the effect of column inclination.Keywords: punching shear, non-linear finite element, inclined columns, reinforced concrete connection
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