Search results for: full-potential KKR-green’s function method
22027 Numerical Simulation of Unsteady Natural Convective Nanofluid Flow within a Trapezoidal Enclosure Using Meshfree Method
Authors: S. Nandal, R. Bhargava
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The paper contains a numerical study of the unsteady magneto-hydrodynamic natural convection flow of nanofluids within a symmetrical wavy walled trapezoidal enclosure. The length and height of enclosure are both considered equal to L. Two-phase nanofluid model is employed. The governing equations of nanofluid flow along with boundary conditions are non-dimensionalized and are solved using one of Meshfree technique (EFGM method). Meshfree numerical technique does not require a predefined mesh for discretization purpose. The bottom wavy wall of the enclosure is defined using a cosine function. Element free Galerkin method (EFGM) does not require the domain. The effects of various parameters namely time t, amplitude of bottom wavy wall a, Brownian motion parameter Nb and thermophoresis parameter Nt is examined on rate of heat and mass transfer to get a visualization of cooling and heating effects. Such problems have important applications in heat exchangers or solar collectors, as wavy walled enclosures enhance heat transfer in comparison to flat walled enclosures.Keywords: heat transfer, meshfree methods, nanofluid, trapezoidal enclosure
Procedia PDF Downloads 15822026 Forecasting of COVID-19 Cases, Hospitalization Admissions, and Death Cases Based on Wastewater Sars-COV-2 Surveillance Using Copula Time Series Model
Authors: Hueiwang Anna Jeng, Norou Diawara, Nancy Welch, Cynthia Jackson, Rekha Singh, Kyle Curtis, Raul Gonzalez, David Jurgens, Sasanka Adikari
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Modeling effort is needed to predict the COVID-19 trends for developing management strategies and adaptation measures. The objective of this study was to assess whether SARS-CoV-2 viral load in wastewater could serve as a predictor for forecasting COVID-19 cases, hospitalization cases, and death cases using copula-based time series modeling. SARS-CoV-2 RNA load in raw wastewater in Chesapeake VA was measured using the RT-qPCR method. Gaussian copula time series marginal regression model, incorporating an autoregressive moving average model and the copula function, served as a forecasting model. COVID-19 cases were correlated with wastewater viral load, hospitalization cases, and death cases. The forecasted trend of COVID-19 cases closely paralleled one of the reported cases, with over 90% of the forecasted COVID-19 cases falling within the 99% confidence interval of the reported cases. Wastewater SARS-CoV-2 viral load could serve as a predictor for COVID-19 cases and hospitalization cases.Keywords: COVID-19, modeling, time series, copula function
Procedia PDF Downloads 6922025 The Structure and Function Investigation and Analysis of the Automatic Spin Regulator (ASR) in the Powertrain System of Construction and Mining Machines with the Focus on Dump Trucks
Authors: Amir Mirzaei
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The powertrain system is one of the most basic and essential components in a machine. The occurrence of motion is practically impossible without the presence of this system. When power is generated by the engine, it is transmitted by the powertrain system to the wheels, which are the last parts of the system. Powertrain system has different components according to the type of use and design. When the force generated by the engine reaches to the wheels, the amount of frictional force between the tire and the ground determines the amount of traction and non-slip or the amount of slip. At various levels, such as icy, muddy, and snow-covered ground, the amount of friction coefficient between the tire and the ground decreases dramatically and considerably, which in turn increases the amount of force loss and the vehicle traction decreases drastically. This condition is caused by the phenomenon of slipping, which, in addition to the waste of energy produced, causes the premature wear of driving tires. It also causes the temperature of the transmission oil to rise too much, as a result, causes a reduction in the quality and become dirty to oil and also reduces the useful life of the clutches disk and plates inside the transmission. this issue is much more important in road construction and mining machinery than passenger vehicles and is always one of the most important and significant issues in the design discussion, in order to overcome. One of these methods is the automatic spin regulator system which is abbreviated as ASR. The importance of this method and its structure and function have solved one of the biggest challenges of the powertrain system in the field of construction and mining machinery. That this research is examined.Keywords: automatic spin regulator, ASR, methods of reducing slipping, methods of preventing the reduction of the useful life of clutches disk and plate, methods of preventing the premature dirtiness of transmission oil, method of preventing the reduction of the useful life of tires
Procedia PDF Downloads 7922024 Developing a Hybrid Method to Diagnose and Predict Sports Related Concussions with Machine Learning
Authors: Melody Yin
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Concussions impact a large amount of adolescents; they make up as much as half of the diagnosed concussions in America. This research proposes a hybrid machine learning model based on the combination of human/knowledge-based domains and computer-generated feature rankings to improve the accuracy of diagnosing sports related concussion (SRC). Using a data set of symptoms collected on the sideline post-SRC events, the symptom selection criteria method has been developed by using Google AutoML's important score function to identify the top 10 symptom features. In addition, symptom domains have been introduced as another parameter, categorizing the symptoms into physical, cognitive, sleep, and emotional domains. The hybrid machine learning model has been trained with a combination of the top 10 symptoms and 4 domains. From the results, the hybrid model was the best performer for symptom resolution time prediction in 2 and 4-week thresholds. This research is a proof of concept study in the use of domains along with machine learning in order to improve concussion prediction accuracy. It is also possible that the use of domains can make the model more efficient due to reduced training time. This research examines the use of a hybrid method in predicting sports-related concussion. This achievement is based on data preprocessing, using a hybrid method to select criteria to achieve high performance.Keywords: hybrid model, machine learning, sports related concussion, symptom resolution time
Procedia PDF Downloads 16822023 Theoretical Comparisons and Empirical Illustration of Malmquist, Hicks–Moorsteen, and Luenberger Productivity Indices
Authors: Fatemeh Abbasi, Sahand Daneshvar
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Productivity is one of the essential goals of companies to improve performance, which as a strategy-oriented method, determines the basis of the company's economic growth. The history of productivity goes back centuries, but most researchers defined productivity as the relationship between a product and the factors used in production in the early twentieth century. Productivity as the optimal use of available resources means that "more output using less input" can increase companies' economic growth and prosperity capacity. Also, having a quality life based on economic progress depends on productivity growth in that society. Therefore, productivity is a national priority for any developed country. There are several methods for calculating productivity growth measurements that can be divided into parametric and non-parametric methods. Parametric methods rely on the existence of a function in their hypotheses, while non-parametric methods do not require a function based on empirical evidence. One of the most popular non-parametric methods is Data Envelopment Analysis (DEA), which measures changes in productivity over time. The DEA evaluates the productivity of decision-making units (DMUs) based on mathematical models. This method uses multiple inputs and outputs to compare the productivity of similar DMUs such as banks, government agencies, companies, airports, Etc. Non-parametric methods are themselves divided into the frontier and non frontier approaches. The Malmquist productivity index (MPI) proposed by Caves, Christensen, and Diewert (1982), the Hicks–Moorsteen productivity index (HMPI) proposed by Bjurek (1996), or the Luenberger productivity indicator (LPI) proposed by Chambers (2002) are powerful tools for measuring productivity changes over time. This study will compare the Malmquist, Hicks–Moorsteen, and Luenberger indices theoretically and empirically based on DEA models and review their strengths and weaknesses.Keywords: data envelopment analysis, Hicks–Moorsteen productivity index, Leuenberger productivity indicator, malmquist productivity index
Procedia PDF Downloads 19422022 Influence of Annealing Temperature on Optical, Anticandidal, Photocatalytic and Dielectric Properties of ZnO/TiO2 Nanocomposites
Authors: Wasi Khan, Suboohi Shervani, Swaleha Naseem, Mohd. Shoeb, J. A. Khan, B. R. Singh, A. H. Naqvi
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We have successfully synthesized ZnO/TiO2 nanocomposite using a two-step solochemical synthesis method. The influence of annealing temperature on microstructural, optical, anticandidal, photocatalytic activities and dielectric properties were investigated. X-ray diffraction (XRD) and scanning electron microscopy (SEM) show the formation of nanocomposite and uniform surface morphology of all samples. The UV-Vis spectra indicate decrease in band gap energy with increase in annealing temperature. The anticandidal activity of ZnO/TiO2 nanocomposite was evaluated against MDR C. albicans 077. The in-vitro killing assay revealed that the ZnO/TiO2 nanocomposite efficiently inhibit the growth of the C. albicans 077. The nanocomposite also exhibited the photocatalytic activity for the degradation of methyl orange as a function of time at 465 nm wavelength. The electrical behaviour of composite has been studied over a wide range of frequencies at room temperature using complex impedance spectroscopy. The dielectric constants, dielectric loss and ac conductivity (σac) were studied as the function of frequency, which have been explained by ‘Maxwell Wagner Model’. The data reveals that the dielectric constant and loss (tanδ) exhibit the normal dielectric behavior and decreases with the increase in frequency.Keywords: ZnO/TiO2 nanocomposites, SEM, photocatalytic activity, dielectric properties
Procedia PDF Downloads 40622021 Estimation and Restoration of Ill-Posed Parameters for Underwater Motion Blurred Images
Authors: M. Vimal Raj, S. Sakthivel Murugan
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Underwater images degrade their quality due to atmospheric conditions. One of the major problems in an underwater image is motion blur caused by the imaging device or the movement of the object. In order to rectify that in post-imaging, parameters of the blurred image are to be estimated. So, the point spread function is estimated by the properties, using the spectrum of the image. To improve the estimation accuracy of the parameters, Optimized Polynomial Lagrange Interpolation (OPLI) method is implemented after the angle and length measurement of motion-blurred images. Initially, the data were collected from real-time environments in Chennai and processed. The proposed OPLI method shows better accuracy than the existing classical Cepstral, Hough, and Radon transform estimation methods for underwater images.Keywords: image restoration, motion blur, parameter estimation, radon transform, underwater
Procedia PDF Downloads 17622020 A Study on Inverse Determination of Impact Force on a Honeycomb Composite Panel
Authors: Hamed Kalhori, Lin Ye
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In this study, an inverse method was developed to reconstruct the magnitude and duration of impact forces exerted to a rectangular carbon fibre-epoxy composite honeycomb sandwich panel. The dynamic signals captured by Piezoelectric (PZT) sensors installed on the panel remotely from the impact locations were utilized to reconstruct the impact force generated by an instrumented hammer through an extended deconvolution approach. Two discretized forms of convolution integral are considered; the traditional one with an explicit transfer function and the modified one without an explicit transfer function. Deconvolution, usually applied to reconstruct the time history (e.g. magnitude) of a stochastic force at a defined location, is extended to identify both the location and magnitude of the impact force among a number of potential impact locations. It is assumed that a number of impact forces are simultaneously exerted to all potential locations, but the magnitude of all forces except one is zero, implicating that the impact occurs only at one location. The extended deconvolution is then applied to determine the magnitude as well as location (among the potential ones), incorporating the linear superposition of responses resulted from impact at each potential location. The problem can be categorized into under-determined (the number of sensors is less than that of impact locations), even-determined (the number of sensors equals that of impact locations), or over-determined (the number of sensors is greater than that of impact locations) cases. For an under-determined case, it comprises three potential impact locations and one PZT sensor for the rectangular carbon fibre-epoxy composite honeycomb sandwich panel. Assessments are conducted to evaluate the factors affecting the precision of the reconstructed force. Truncated Singular Value Decomposition (TSVD) and the Tikhonov regularization are independently chosen to regularize the problem to find the most suitable method for this system. The selection of optimal value of the regularization parameter is investigated through L-curve and Generalized Cross Validation (GCV) methods. In addition, the effect of different width of signal windows on the reconstructed force is examined. It is observed that the impact force generated by the instrumented impact hammer is sensitive to the impact locations of the structure, having a shape from a simple half-sine to a complicated one. The accuracy of the reconstructed impact force is evaluated using the correlation co-efficient between the reconstructed force and the actual one. Based on this criterion, it is concluded that the forces reconstructed by using the extended deconvolution without an explicit transfer function together with Tikhonov regularization match well with the actual forces in terms of magnitude and duration.Keywords: honeycomb composite panel, deconvolution, impact localization, force reconstruction
Procedia PDF Downloads 53522019 Elvis Improved Method for Solving Simultaneous Equations in Two Variables with Some Applications
Authors: Elvis Adam Alhassan, Kaiyu Tian, Akos Konadu, Ernest Zamanah, Michael Jackson Adjabui, Ibrahim Justice Musah, Esther Agyeiwaa Owusu, Emmanuel K. A. Agyeman
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In this paper, how to solve simultaneous equations using the Elvis improved method is shown. The Elvis improved method says; to make one variable in the first equation the subject; make the same variable in the second equation the subject; equate the results and simplify to obtain the value of the unknown variable; put the value of the variable found into one equation from the first or second steps and simplify for the remaining unknown variable. The difference between our Elvis improved method and the substitution method is that: with Elvis improved method, the same variable is made the subject in both equations, and the two resulting equations equated, unlike the substitution method where one variable is made the subject of only one equation and substituted into the other equation. After describing the Elvis improved method, findings from 100 secondary students and the views of 5 secondary tutors to demonstrate the effectiveness of the method are presented. The study's purpose is proved by hypothetical examples.Keywords: simultaneous equations, substitution method, elimination method, graphical method, Elvis improved method
Procedia PDF Downloads 13722018 An Improved Total Variation Regularization Method for Denoising Magnetocardiography
Authors: Yanping Liao, Congcong He, Ruigang Zhao
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The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.Keywords: constraint parameters, derivative matrix, magnetocardiography, regular term, total variation
Procedia PDF Downloads 15322017 A Design for Supply Chain Model by Integrated Evaluation of Design Value and Supply Chain Cost
Authors: Yuan-Jye Tseng, Jia-Shu Li
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To design a product with the given product requirement and design objective, there can be alternative ways to propose the detailed design specifications of the product. In the design modeling stage, alternative design cases with detailed specifications can be modeled to fulfill the product requirement and design objective. Therefore, in the design evaluation stage, it is required to perform an evaluation of the alternative design cases for deciding the final design. The purpose of this research is to develop a product evaluation model for evaluating the alternative design cases by integrated evaluating the criteria of functional design, Kansei design, and design for supply chain. The criteria in the functional design group include primary function, expansion function, improved function, and new function. The criteria in the Kansei group include geometric shape, dimension, surface finish, and layout. The criteria in the design for supply chain group include material, manufacturing process, assembly, and supply chain operation. From the point of view of value and cost, the criteria in the functional design group and Kansei design group represent the design value of the product. The criteria in the design for supply chain group represent the supply chain and manufacturing cost of the product. It is required to evaluate the design value and the supply chain cost to determine the final design. For the purpose of evaluating the criteria in the three criteria groups, a fuzzy analytic network process (FANP) method is presented to evaluate a weighted index by calculating the total relational values among the three groups. A method using the technique for order preference by similarity to ideal solution (TOPSIS) is used to compare and rank the design alternative cases according to the weighted index using the total relational values of the criteria. The final decision of a design case can be determined by using the ordered ranking. For example, the design case with the top ranking can be selected as the final design case. Based on the criteria in the evaluation, the design objective can be achieved with a combined and weighted effect of the design value and manufacturing cost. An example product is demonstrated and illustrated in the presentation. It shows that the design evaluation model is useful for integrated evaluation of functional design, Kansei design, and design for supply chain to determine the best design case and achieve the design objective.
Keywords: design for supply chain, design evaluation, functional design, Kansei design, fuzzy analytic network process, technique for order preference by similarity to ideal solution
Procedia PDF Downloads 31822016 An Algorithm to Find Fractional Edge Domination Number and Upper Fractional Edge Domination Number of an Intuitionistic Fuzzy Graph
Authors: Karunambigai Mevani Govindasamy, Sathishkumar Ayyappan
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In this paper, we formulate the algorithm to find out the dominating function parameters of Intuitionistic Fuzzy Graphs(IFG). The methodology we adopted here is converting any physical problem into an IFG, and that has been transformed into Intuitionistic Fuzzy Matrix. Using Linear Program Solver software (LiPS), we found the defined parameters for the given IFG. We obtained these parameters for a path and cycle IFG. This study can be extended to other varieties of IFG. In particular, we obtain the definition of edge dominating function, minimal edge dominating function, fractional edge domination number (γ_if^') and upper fractional edge domination number (Γ_if^') of an intuitionistic fuzzy graph. Also, we formulated an algorithm which is appropriate to work on LiPS to find fractional edge domination number and upper fractional edge domination number of an IFG.Keywords: fractional edge domination number, intuitionistic fuzzy cycle, intuitionistic fuzzy graph, intuitionistic fuzzy path
Procedia PDF Downloads 17422015 Application of Genetic Algorithm with Multiobjective Function to Improve the Efficiency of Photovoltaic Thermal System
Authors: Sonveer Singh, Sanjay Agrawal, D. V. Avasthi, Jayant Shekhar
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The aim of this paper is to improve the efficiency of photovoltaic thermal (PVT) system with the help of Genetic Algorithms with multi-objective function. There are some parameters that affect the efficiency of PVT system like depth and length of the channel, velocity of flowing fluid through the channel, thickness of the tedlar and glass, temperature of inlet fluid i.e. all above parameters are considered for optimization. An attempt has been made to the model and optimizes the parameters of glazed hybrid single channel PVT module when two objective functions have been considered separately. The two objective function for optimization of PVT module is overall electrical and thermal efficiency. All equations for PVT module have been derived. Using genetic algorithms (GAs), above two objective functions of the system has been optimized separately and analysis has been carried out for two cases. Two cases are: Case-I; Improvement in electrical and thermal efficiency when overall electrical efficiency is optimized, Case-II; Improvement in electrical and thermal efficiency when overall thermal efficiency is optimized. All the parameters that are used in genetic algorithms are the parameters that could be changed, and the non-changeable parameters, like solar radiation, ambient temperature cannot be used in the algorithm. It has been observed that electrical efficiency (14.08%) and thermal efficiency (19.48%) are obtained when overall thermal efficiency was an objective function for optimization. It is observed that GA is a very efficient technique to estimate the design parameters of hybrid single channel PVT module.Keywords: genetic algorithm, energy, exergy, PVT module, optimization
Procedia PDF Downloads 60522014 Exercise and Aging Process Related to Oxidative Stress
Authors: B. Dejanova, S. Petrovska, L. Todorovska, J. Pluncevic, S. Mancevska, V. Antevska, E. Sivevska, I. Karagjozova
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Introduction: Aging process is mainly related to endothelial function which may be impaired by oxidative stress (OS). Exercise is known to be beneficial to aging process, which may improve health and prevent appearance of chronic diseases in elderly. The aim of the study was to investigate the OS markers related to exercise. Methods: A number of 80 subjects (healthy volunteers) were examined (38 male and 32 female), divided in 3 age groups: group I ≤ 30 years (n=24); group II – 31-50 years (n=24); group III - ≥ 51 year (n=32). Each group was divided to subgroups of sedentary subjects (SS) and subjects who exercise (SE). Group I: SS (n=11), SE (n=13); group II: SS (n=13), SE (n=10); group III: SS (n=23) SE (n=9). Lipid peroxidation (LP) as a fluorimetric method with thiobarbituric acid was used to estimate OS. Antioxidative status was determined by cell antioxidants such as enzymes - superoxide dismutase (SOD), glutathione peroxidase (GPx) and glucose 6 phosphate (G-6-PD); and by extra cell antioxidants such as glutathione reductase (GR), nitric oxide (NO) and total antioxidant capacity (TAC). Results: Increased values of LP were noticed along the aging process: group I – 3.30±0.3 µmol/L; group II – 3.91±0.2 µmol/L; group III – 3.94±0.8 µmol/L (p<0.05), while no statistical significance was found between male and female subjects. Statistical significance for OS was not found between SS and SE in group I as it was found in group II (p<0.05) and in group III (p<0.01). No statistical significance was found for all cell antioxidants and GR within the groups, while NO and TAC showed lower values in SS compared to SE in II (p<0.05) and in group III (p<0.05). Discussion and conclusion: Aging process showed increased OS which may be either due to impaired function of scavengers of free radicals or due to their enormous production. Well balanced exercise might be one of the factors that keep the integrity of blood vessel endothelium which slows down the aging process. Possible mechanism of exercise beneficial influence is shear stress by upregulation of genes coding for nitric oxide bioavailability. Thus, due to obtained results we may conclude that OS is found to be diminished in the subject groups who perform exercise.Keywords: oxidative stress, aging process, exercise, endothelial function
Procedia PDF Downloads 38722013 Theoretical Analysis of the Solid State and Optical Characteristics of Calcium Sulpide Thin Film
Authors: Emmanuel Ifeanyi Ugwu
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Calcium Sulphide which is one of Chalcogenide group of thin films has been analyzed in this work using a theoretical approach in which a scalar wave was propagated through the material thin film medium deposited on a glass substrate with the assumption that the dielectric medium has homogenous reference dielectric constant term, and a perturbed dielectric function, representing the deposited thin film medium on the surface of the glass substrate as represented in this work. These were substituted into a defined scalar wave equation that was solved first of all by transforming it into Volterra equation of second type and solved using the method of separation of variable on scalar wave and subsequently, Green’s function technique was introduced to obtain a model equation of wave propagating through the thin film that was invariably used in computing the propagated field, for different input wavelengths representing UV, Visible and Near-infrared regions of field considering the influence of the dielectric constants of the thin film on the propagating field. The results obtained were used in turn to compute the band gaps, solid state and optical properties of the thin film.Keywords: scalar wave, dielectric constant, calcium sulphide, solid state, optical properties
Procedia PDF Downloads 11822012 The Survey of Sexual Health and Pornography among Divorce-Asking Women in West Azerbaijan-Iran: A Cross-Sectional Study
Authors: Soheila Rabiepoor, Elham Sadeghi
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Introduction: Divorce is both a personal and a social issue. Nowadays, due to various factors such as rapid social, economical, and cultural changes, the family structure has undergone many rough changes, out of 3 marriages 2 of them lead to divorce. One of the factors affecting the incidence of divorce and relationship problems between couples is the sexual and marital behaviors. There are several different reasons to suspect that pornography might affect divorce in either a positive or a negative way. Therefore this study evaluated the sexual health of divorce-asking in Urmia, Iran. Methods: This was a cross-sectional descriptive study and was conducted on 71 married women of Urmia, Iran in 2016. Participants were applicants of divorce (referred to divorce center) who were selected by using convenient sampling method. Data gathering tool included the scales for measuring demographic, sexual health (sexual satisfaction and function), and researcher made pornography questions. Data were analyzed based on the SPSS 16 software. P-values less than 0.05 were considered significant. Results: Investigation of demographic features showed that age average of studied samples was 28.98 ± 7.44, with a marriage duration average 8.12 ± 6.53 years (min 1 year/ max 28 years). Most of their education was at diploma (45.1%). 69 % of the women declared their income and expenditure as equal. Nearly 42% of women and 59% of their partner had watched sexual pornography clips. 45.5% of participants reported that they compared own sexual relationship with sexual pornography clips. In the other hand, sexual satisfaction total score was 51.50 ± 17.92. The mean total sexual function score was 16.62 ± 10.58. According to these findings, most of women were experienced sexual dissatisfaction and dysfunction. Conclusions: The results of the study indicated that who had low sexual satisfaction score, had higher rate of watching pornography clips. Based on current study, paying attention to family education and counseling programs especially in the sexual field will be more fruitful.Keywords: divorce-asking, pornography, sexual satisfaction, sexual function, women
Procedia PDF Downloads 58522011 A Semiparametric Approach to Estimate the Mode of Continuous Multivariate Data
Authors: Tiee-Jian Wu, Chih-Yuan Hsu
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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method
Procedia PDF Downloads 28522010 On Figuring the City Characteristics and Landscape in Overall Urban Design: A Case Study in Xiangyang Central City, China
Authors: Guyue Zhu, Liangping Hong
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Chinese overall urban design faces a large number of problems such as the neglect of urban characteristics, generalization of content, and difficulty in implementation. Focusing on these issues, this paper proposes the main points of shaping urban characteristics in overall urban design: focuses on core problems in city function and scale, landscape pattern, historical culture, social resources and modern city style and digs the urban characteristic genes. Then, we put forward “core problem location and characteristic gene enhancement” as a kind of overall urban design technical method. Firstly, based on the main problems in urban space as a whole, for the operability goal, the method extracts the key genes and integrates into the multi-dimension system in a targeted manner. Secondly, hierarchical management and guidance system is established which may be in line with administrative management. Finally, by converting the results, action plan is drawn up that can be dynamically implemented. Based on the above idea and method, a practical exploration has been performed in the case of Xiangyang central city.Keywords: city characteristics, overall urban design, planning implementation, Xiangyang central city
Procedia PDF Downloads 14922009 Pantograph-Catenary Contact Force: Features Evaluation for Catenary Diagnostics
Authors: Mehdi Brahimi, Kamal Medjaher, Noureddine Zerhouni, Mohammed Leouatni
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The Prognostics and Health Management is a system engineering discipline which provides solutions and models to the implantation of a predictive maintenance. The approach is based on extracting useful information from monitoring data to assess the “health” state of an industrial equipment or an asset. In this paper, we examine multiple extracted features from Pantograph-Catenary contact force in order to select the most relevant ones to achieve a diagnostics function. The feature extraction methodology is based on simulation data generated thanks to a Pantograph-Catenary simulation software called INPAC and measurement data. The feature extraction method is based on both statistical and signal processing analyses. The feature selection method is based on statistical criteria.Keywords: catenary/pantograph interaction, diagnostics, Prognostics and Health Management (PHM), quality of current collection
Procedia PDF Downloads 29022008 Improving the Efficiency of a High Pressure Turbine by Using Non-Axisymmetric Endwall: A Comparison of Two Optimization Algorithms
Authors: Abdul Rehman, Bo Liu
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Axial flow turbines are commonly designed with high loads that generate strong secondary flows and result in high secondary losses. These losses contribute to almost 30% to 50% of the total losses. Non-axisymmetric endwall profiling is one of the passive control technique to reduce the secondary flow loss. In this paper, the non-axisymmetric endwall profile construction and optimization for the stator endwalls are presented to improve the efficiency of a high pressure turbine. The commercial code NUMECA Fine/ Design3D coupled with Fine/Turbo was used for the numerical investigation, design of experiments and the optimization. All the flow simulations were conducted by using steady RANS and Spalart-Allmaras as a turbulence model. The non-axisymmetric endwalls of stator hub and shroud were created by using the perturbation law based on Bezier Curves. Each cut having multiple control points was supposed to be created along the virtual streamlines in the blade channel. For the design of experiments, each sample was arbitrarily generated based on values automatically chosen for the control points defined during parameterization. The Optimization was achieved by using two algorithms i.e. the stochastic algorithm and gradient-based algorithm. For the stochastic algorithm, a genetic algorithm based on the artificial neural network was used as an optimization method in order to achieve the global optimum. The evaluation of the successive design iterations was performed using artificial neural network prior to the flow solver. For the second case, the conjugate gradient algorithm with a three dimensional CFD flow solver was used to systematically vary a free-form parameterization of the endwall. This method is efficient and less time to consume as it requires derivative information of the objective function. The objective function was to maximize the isentropic efficiency of the turbine by keeping the mass flow rate as constant. The performance was quantified by using a multi-objective function. Other than these two classifications of the optimization methods, there were four optimizations cases i.e. the hub only, the shroud only, and the combination of hub and shroud. For the fourth case, the shroud endwall was optimized by using the optimized hub endwall geometry. The hub optimization resulted in an increase in the efficiency due to more homogenous inlet conditions for the rotor. The adverse pressure gradient was reduced but the total pressure loss in the vicinity of the hub was increased. The shroud optimization resulted in an increase in efficiency, total pressure loss and entropy were reduced. The combination of hub and shroud did not show overwhelming results which were achieved for the individual cases of the hub and the shroud. This may be caused by fact that there were too many control variables. The fourth case of optimization showed the best result because optimized hub was used as an initial geometry to optimize the shroud. The efficiency was increased more than the individual cases of optimization with a mass flow rate equal to the baseline design of the turbine. The results of artificial neural network and conjugate gradient method were compared.Keywords: artificial neural network, axial turbine, conjugate gradient method, non-axisymmetric endwall, optimization
Procedia PDF Downloads 22522007 DNpro: A Deep Learning Network Approach to Predicting Protein Stability Changes Induced by Single-Site Mutations
Authors: Xiao Zhou, Jianlin Cheng
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A single amino acid mutation can have a significant impact on the stability of protein structure. Thus, the prediction of protein stability change induced by single site mutations is critical and useful for studying protein function and structure. Here, we presented a deep learning network with the dropout technique for predicting protein stability changes upon single amino acid substitution. While using only protein sequence as input, the overall prediction accuracy of the method on a standard benchmark is >85%, which is higher than existing sequence-based methods and is comparable to the methods that use not only protein sequence but also tertiary structure, pH value and temperature. The results demonstrate that deep learning is a promising technique for protein stability prediction. The good performance of this sequence-based method makes it a valuable tool for predicting the impact of mutations on most proteins whose experimental structures are not available. Both the downloadable software package and the user-friendly web server (DNpro) that implement the method for predicting protein stability changes induced by amino acid mutations are freely available for the community to use.Keywords: bioinformatics, deep learning, protein stability prediction, biological data mining
Procedia PDF Downloads 46822006 Multi-Atlas Segmentation Based on Dynamic Energy Model: Application to Brain MR Images
Authors: Jie Huo, Jonathan Wu
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Segmentation of anatomical structures in medical images is essential for scientific inquiry into the complex relationships between biological structure and clinical diagnosis, treatment and assessment. As a method of incorporating the prior knowledge and the anatomical structure similarity between a target image and atlases, multi-atlas segmentation has been successfully applied in segmenting a variety of medical images, including the brain, cardiac, and abdominal images. The basic idea of multi-atlas segmentation is to transfer the labels in atlases to the coordinate of the target image by matching the target patch to the atlas patch in the neighborhood. However, this technique is limited by the pairwise registration between target image and atlases. In this paper, a novel multi-atlas segmentation approach is proposed by introducing a dynamic energy model. First, the target is mapped to each atlas image by minimizing the dynamic energy function, then the segmentation of target image is generated by weighted fusion based on the energy. The method is tested on MICCAI 2012 Multi-Atlas Labeling Challenge dataset which includes 20 target images and 15 atlases images. The paper also analyzes the influence of different parameters of the dynamic energy model on the segmentation accuracy and measures the dice coefficient by using different feature terms with the energy model. The highest mean dice coefficient obtained with the proposed method is 0.861, which is competitive compared with the recently published method.Keywords: brain MRI segmentation, dynamic energy model, multi-atlas segmentation, energy minimization
Procedia PDF Downloads 33622005 Toxicity Analysis of Metal Coating Industry Wastewaters by Phytotoxicity Method
Authors: Sukru Dursun, Zeynep Cansu Ayturan, Mostafa Maroof
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Metal coating which is important method used for protecting metals against oxidation and corrosion, decreasing friction, protecting metals from chemicals, easing cleaning of the metals. There are several methods used for metal coating such as hot-dip galvanizing, thermal spraying, electroplating and sherardizing. Method which will be used for metal coating depends on the type of metal. The materials mostly used for coating are zinc, nickel, brass, chrome, gold, cadmium, copper, brass, and silver. Within these materials, chrome ion has significant negative impacts on human, other living organisms and environment. Moreover, especially on human chrome may cause lung cancer, stomach ulcer, kidney and liver function disorders and death. Therefore, wastewaters of metal coating industry including chrome should be treated very carefully. In this study, wastewater containing chrome produced by metal coating industry was analysed with phytotoxicity method that is based on measuring the reaction of some plant species against different concentrations of chrome solution. Main plants used for phytotoxicity tests are Lepidium sativum and Lemna minor. Owing to phytotoxicity test, assessing the negative effects of chrome which may harm plants and offering more accurate wastewater treatment techniques against chromium wastewater is possible. Furthermore, the results taken from phytotoxicity tests were analysed with respect to their variance and their importance against different concentrations of chrome solution were determined.Keywords: metal coating wastewater, chrome, phytotoxicity, Lepidium sativum, Lemna minor
Procedia PDF Downloads 32322004 Design of IMC-PID Controller Cascaded Filter for Simplified Decoupling Control System
Authors: Le Linh, Truong Nguyen Luan Vu, Le Hieu Giang
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In this work, the IMC-PID controller cascaded filter based on Internal Model Control (IMC) scheme is systematically proposed for the simplified decoupling control system. The simplified decoupling is firstly introduced for multivariable processes by using coefficient matching to obtain a stable, proper, and causal simplified decoupler. Accordingly, transfer functions of decoupled apparent processes can be expressed as a set of n equivalent independent processes and then derived as a ratio of the original open-loop transfer function to the diagonal element of the dynamic relative gain array. The IMC-PID controller in series with filter is then directly employed to enhance the overall performance of the decoupling control system while avoiding difficulties arising from properties inherent to simplified decoupling. Some simulation studies are considered to demonstrate the simplicity and effectiveness of the proposed method. Simulations were conducted by tuning various controllers of the multivariate processes with multiple time delays. The results indicate that the proposed method consistently performs well with fast and well-balanced closed-loop time responses.Keywords: coefficient matching method, internal model control (IMC) scheme, PID controller cascaded filter, simplified decoupler
Procedia PDF Downloads 44222003 Developing a Structured Example Space for Finding the Collision Points of Functions and Their Inverse
Authors: M. Saeed, A. Shahidzadeh
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Interaction between teachers and learners requires applying a set of samples (examples) which helps to create coordination between the goals and methods. The main result and achievement and application of samples (examples) are that they can bring the teacher and learner to a shared understanding of the concept. mathematical concepts, and also one of the challenging issues in the discussion of the function is to find the collision points of functions of and, regarding that the example space of teachers is different in this issue, this paper aims to present an example space including several problems of the secondary school with the help of intuition and drawing various graphs of functions of and for more familiarity of teachers.Keywords: inverse function, educational example, Mathematic example, example space
Procedia PDF Downloads 17922002 Structural Health Monitoring of Buildings–Recorded Data and Wave Method
Authors: Tzong-Ying Hao, Mohammad T. Rahmani
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This article presents the structural health monitoring (SHM) method based on changes in wave traveling times (wave method) within a layered 1-D shear beam model of structure. The wave method measures the velocity of shear wave propagating in a building from the impulse response functions (IRF) obtained from recorded data at different locations inside the building. If structural damage occurs in a structure, the velocity of wave propagation through it changes. The wave method analysis is performed on the responses of Torre Central building, a 9-story shear wall structure located in Santiago, Chile. Because events of different intensity (ambient vibrations, weak and strong earthquake motions) have been recorded at this building, therefore it can serve as a full-scale benchmark to validate the structural health monitoring method utilized. The analysis of inter-story drifts and the Fourier spectra for the EW and NS motions during 2010 Chile earthquake are presented. The results for the NS motions suggest the coupling of translation and torsion responses. The system frequencies (estimated from the relative displacement response of the 8th-floor with respect to the basement from recorded data) were detected initially decreasing approximately 24% in the EW motion. Near the end of shaking, an increase of about 17% was detected. These analysis and results serve as baseline indicators of the occurrence of structural damage. The detected changes in wave velocities of the shear beam model are consistent with the observed damage. However, the 1-D shear beam model is not sufficient to simulate the coupling of translation and torsion responses in the NS motion. The wave method is proven for actual implementation in structural health monitoring systems based on carefully assessing the resolution and accuracy of the model for its effectiveness on post-earthquake damage detection in buildings.Keywords: Chile earthquake, damage detection, earthquake response, impulse response function, shear beam model, shear wave velocity, structural health monitoring, torre central building, wave method
Procedia PDF Downloads 36822001 Two-Step Inversion Method for Multi-mode Surface Waves
Authors: Ying Zhang
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Surface waves provide critical constraints about the earth's structure in the crust and upper mantle. However, different modes of Love waves with close group velocities often arrive at a similar time and interfere with each other. This problem is typical for Love waves at intermediate periods that travel through the oceanic lithosphere. Therefore, we developed a two-step inversion approach to separate the waveforms of the fundamental and first higher mode of Love waves. We first solve the phase velocities of the two modes and their amplitude ratios. The misfit function is based on the sum of phase differences among the station pairs. We then solve the absolute amplitudes of the two modes and their initial phases using obtained phase velocities and amplitude ratio. The separated waveforms of each mode from the two-step inversion method can be further used in surface wave tomography to improve model resolution.Keywords: surface wave inversion, waveform separation, love waves, higher-mode interference
Procedia PDF Downloads 7022000 Study on Optimal Control Strategy of PM2.5 in Wuhan, China
Authors: Qiuling Xie, Shanliang Zhu, Zongdi Sun
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In this paper, we analyzed the correlation relationship among PM2.5 from other five Air Quality Indices (AQIs) based on the grey relational degree, and built a multivariate nonlinear regression equation model of PM2.5 and the five monitoring indexes. For the optimal control problem of PM2.5, we took the partial large Cauchy distribution of membership equation as satisfaction function. We established a nonlinear programming model with the goal of maximum performance to price ratio. And the optimal control scheme is given.Keywords: grey relational degree, multiple linear regression, membership function, nonlinear programming
Procedia PDF Downloads 29921999 Pyrroloquinoline Quinone Enhances the Mitochondrial Function by Increasing Beta-Oxidation and a Balanced Mitochondrial Recycling in Mice Granulosa Cells
Authors: Moustafa Elhamouly, Masayuki Shimada
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The production of competent oocytes is essential for reproductivity in mammals. Maintenance of mitochondrial efficiency is required to supply the ATP necessary for granulosa cell proliferation during the follicular development process. Treatment with Pyrroloquinoline quinone (PQQ) has been reported to increase the number of ovulated oocytes and pups per delivery in mice by maintaining healthy mitochondrial function. This study aimed to elucidate how PQQ maintains mitochondrial function during ovarian follicle growth. To do this, both in vitro and in vivo experiments were performed with granulosa cells from superovulated immature (3-week-old) mice that were pretreated with or without PQQ. The effects of PQQ on beta-oxidation, mitochondrial function, mitophagy, and mitochondrial biogenesis were examined. PQQ increased beta-oxidation-related genes and CPT1 protein content in granulosa cells and this was associated with a decreased phosphorylation of P38 signaling protein. Using the fatty acid oxidation assay on the flux analyzer, PQQ increased the reliance of beta-oxidation on the endogenous fatty acids and was associated with a mild UCP-dependant mitochondrial uncoupling, ATP production, mitophagy, and mitochondrial biogenesis. PQQ also increased the expression of endogenous antioxidant enzymes. Thus, PQQ induced beta-oxidation in growing granulosa cells relying on endogenous fatty acids. And reduced the Reactive oxygen species (ROS) production by inducing a mild mitochondrial uncoupling with keeping high mitochondrial function. Damaged mitochondria were recycled by the induced mitophagy and replaced by the increased mitochondrial biogenesis. Collectively, PQQ may enhance reproductivity by maintaining the efficiency of mitochondria to produce enough ATP required for normal folliculogenesis.Keywords: granulosa cells, mitochondrial uncoupling, mitophagy, pyrroloquinoline quinone (PQQ), reactive oxygen species (ROS).
Procedia PDF Downloads 8321998 Correlation between Potential Intelligence Explanatory Study in the Perspective of Multiple Intelligence Theory by Using Dermatoglyphics and Culture Approaches
Authors: Efnie Indrianie
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Potential Intelligence constitutes one essential factor in every individual. This intelligence can be a provision for the development of Performance Intelligence if it is supported by surrounding environment. Fingerprint analysis is a method in recognizing this Potential Intelligence. This method is grounded on pattern and number of finger print outlines that are assumed symmetrical with the number of nerves in our brain, in which these areas have their own function among another. These brain’s functions are later being transposed into intelligence components in accordance with the Multiple Intelligences theory. This research tested the correlation between Potential Intelligence and the components of its Performance Intelligence. Statistical test results that used Pearson correlation showed that five components of Potential Intelligence correlated with Performance Intelligence. Those five components are Logic-Math, Logic, Linguistic, Music, Kinesthetic, and Intrapersonal. Also, this research indicated that cultural factor had a big role in shaping intelligence.Keywords: potential intelligence, performance intelligence, multiple intelligences, fingerprint, environment, brain
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