Search results for: non-linear regression models

Authors: Hyun-Woo Cho

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Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

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Authors: Gadah Alkeniah

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Leadership is acknowledged internationally as fundamental to school efficiency and school enhancement nevertheless there are various understandings of what leadership is and how it is realised in practice. There are a number of educational leadership models that are considered important. However, the present study uses a systematic review method to examine and compare five models of the most well-known contemporary models of leadership as well as introduces the dimension of each model. Our results reveal that recently the distributed leadership has grown in popularity within the field of education. The study concludes by suggesting future directions in leadership development and education research.

Keywords: distributed leadership, instructional leadership, leadership models, moral leadership, strategic leadership, transformational leadership

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Authors: Muhamad Hafiz Ismail, Ahmad H., Nelfianty M. R.

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The longitudinal study is conducted to identify predictive factors of soccer talent among male players aged 14 to 17 years. Convenience sampling involving elite respondents (n=20) and sub-elite respondents (n=20) male soccer players. Descriptive statistics were reported as frequencies and percentages. The inferential statistical analysis is used to report the status of reliability, independent samples t-test, paired samples t-test, and multiple regression analysis. Generally, there are differences in mean of height, muscular strength, muscular endurance, cardiovascular endurance, task orientation, cognitive anxiety, self-confidence, juggling skills, short pass skills, long pass skills, dribbling skills, and shooting skills for 20 elite players and sub-elite players. Accordingly, there was a significant difference between pre and post-test for thirteen variables of height, weight, fat percentage, muscle strength, muscle endurance, cardiovascular endurance, flexibility, BMI, task orientation, juggling skills, short pass skills, a long pass skills, and dribbling skills. Based on the first predictive factors (physical), second predictive factors (fitness), third predictive factors (psychological), and fourth predictive factors (skills in playing football) pledged to the soccer talent; four multiple regression models were produced. The first predictive factor (physical) contributed 53.5 percent, supported by height and percentage of fat in soccer talents. The second predictive factor (fitness) contributed 63.2 percent and the third predictive factors (psychology) contributed 66.4 percent of soccer talent. The fourth predictive factors (skills) contributed 59.0 percent of soccer talent. The four multiple regression models could be used as a guide for talent scouting for soccer players of the future.

Keywords: soccer talent identification, fitness and physical test, soccer skills test, psychological test

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Authors: Al Omari Mohammed Ahmed

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This paper focuses on Maximum Likelihood Estimator with Covariate. Covariates are incorporated into the Weibull model. Under this regression model with regards to maximum likelihood estimator, the parameters of the covariate, shape parameter, survival function and hazard rate of the Weibull regression distribution with right censored data are estimated. The mean square error (MSE) and absolute bias are used to compare the performance of Weibull regression distribution. For the simulation comparison, the study used various sample sizes and several specific values of the Weibull shape parameter.

Keywords: weibull regression distribution, maximum likelihood estimator, survival function, hazard rate, right censoring

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Authors: Reza Soleimanpour, Ching Tai Ng

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Fibre-composites are widely used in various structures due to their attractive properties such as higher stiffness to mass ratio and better corrosion resistance compared to metallic materials. However, one serious weakness of this composite material is delamination, which is a subsurface separation of laminae. A low level of this barely visible damage can cause a significant reduction in residual compressive strength. In the last decade, the application of guided waves for damage detection has been a topic of significant interest for many researches. Among all guided wave techniques, nonlinear guided wave has shown outstanding sensitivity and capability for detecting different types of damages, e.g. cracks and delaminations. So far, most of researches on applications of nonlinear guided wave have been dedicated to isotropic material, such as aluminium and steel, while only a few works have been done on applications of nonlinear characteristics of guided waves in anisotropic materials. This study investigates the nonlinear interactions of the fundamental antisymmetric lamb wave (A0) with delamination in composite laminates using three-dimensional (3D) explicit finite element (FE) simulations. The nonlinearity considered in this study arises from interactions of two interfaces of sub-laminates at the delamination region, which generates contact acoustic nonlinearity (CAN). The aim of this research is to investigate the phenomena of CAN in composite laminated beams by a series of numerical case studies. In this study interaction of fundamental antisymmetric lamb wave with delamination of different sizes are studied in detail. The results show that the A0 lamb wave interacts with the delaminations generating CAN in the form of higher harmonics, which is a good indicator for determining the existence of delaminations in composite laminates.

Keywords: contact acoustic nonlinearity, delamination, fibre reinforced composite beam, finite element, nonlinear guided waves

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Authors: Hesham A. Elkaranshawy, Amr M. Abdelrazek, Hosam M. Ezzat

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The system of ordinary nonlinear differential equations describing sliding velocity during impact with friction for a three-dimensional rigid-multibody system is developed. No analytical solutions have been obtained before for this highly nonlinear system. Hence, a power series solution is proposed. Since the validity of this solution is limited to its convergence zone, a suitable time step is chosen and at the end of it a new series solution is constructed. For a case study, the trajectory of the sliding velocity using the proposed method is built using 6 time steps, which coincides with a Runge-Kutta solution using 38 time steps.

Keywords: impact with friction, nonlinear ordinary differential equations, power series solutions, rough collision

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Authors: Joel Podgorski, Manouchehr Amini, Annette Johnson, Michael Berg

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One-third of the world’s population relies on groundwater for its drinking water. Natural geogenic arsenic and fluoride contaminate ~10% of wells. Prolonged exposure to high levels of arsenic can result in various internal cancers, while high levels of fluoride are responsible for the development of dental and crippling skeletal fluorosis. In poor urban and rural settings, the provision of drinking water free of geogenic contamination can be a major challenge. In order to efficiently apply limited resources in the testing of wells, water resource managers need to know where geogenically contaminated groundwater is likely to occur. The Groundwater Assessment Platform (GAP) fulfills this need by providing state-of-the-art global arsenic and fluoride contamination hazard maps as well as enabling users to create their own groundwater quality models. The global risk models were produced by logistic regression of arsenic and fluoride measurements using predictor variables of various soil, geological and climate parameters. The maps display the probability of encountering concentrations of arsenic or fluoride exceeding the World Health Organization’s (WHO) stipulated concentration limits of 10 µg/L or 1.5 mg/L, respectively. In addition to a reconsideration of the relevant geochemical settings, these second-generation maps represent a great improvement over the previous risk maps due to a significant increase in data quantity and resolution. For example, there is a 10-fold increase in the number of measured data points, and the resolution of predictor variables is generally 60 times greater. These same predictor variable datasets are available on the GAP platform for visualization as well as for use with a modeling tool. The latter requires that users upload their own concentration measurements and select the predictor variables that they wish to incorporate in their models. In addition, users can upload additional predictor variable datasets either as features or coverages. Such models can represent an improvement over the global models already supplied, since (a) users may be able to use their own, more detailed datasets of measured concentrations and (b) the various processes leading to arsenic and fluoride groundwater contamination can be isolated more effectively on a smaller scale, thereby resulting in a more accurate model. All maps, including user-created risk models, can be downloaded as PDFs. There is also the option to share data in a secure environment as well as the possibility to collaborate in a secure environment through the creation of communities. In summary, GAP provides users with the means to reliably and efficiently produce models specific to their region of interest by making available the latest datasets of predictor variables along with the necessary modeling infrastructure.

Keywords: arsenic, fluoride, groundwater contamination, logistic regression

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Authors: Amira Amamou, Mnaouar Chouchane

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This paper investigates the bifurcation and nonlinear behavior of two degrees of freedom model of a symmetrical balanced rigid rotor supported by two identical journal bearings. The fluid film hydrodynamic reactions are modeled by applying both the short and the long bearing approximation and using half Sommerfeld solution. A numerical integration of equations of the journal centre motion is presented to predict the presence and the size of stable or unstable limit cycles in the neighborhood of the stability critical speed. For their stability margins, a continuation method based on the predictor-corrector mechanism is used. The numerical results of responses show that stability and bifurcation behaviors of periodic motions depend strongly on bearing parameters and its dynamic characteristics.

Keywords: hydrodynamic journal bearing, nonlinear stability, continuation method, bifurcations

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Authors: Maor Farid, Oleg Gendelman

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Equivalent mechanical model of liquid sloshing in partially-filled cylindrical vessel is treated in the cases of free oscillations and of horizontal base excitation. The model is designed to cover both the linear and essentially nonlinear sloshing regimes. The latter fluid behaviour might involve hydraulic impacts interacting with the inner walls of the tank. These impulsive interactions are often modeled by high-power potential and dissipation functions. For the sake of analytical description, we use the traditional approach by modeling the impacts with velocity-dependent restitution coefficient. This modelling is similar to vibro-impact nonlinear energy sink (VI NES) which was recently explored for its vibration mitigation performances and nonlinear response regimes. Steady-state periodic regimes and chaotic strongly modulated responses (CSMR) are detected. Those dynamical regimes were described by the system's slow motion on the slow invariant manifold (SIM). There is a good agreement between the analytical results and numerical simulations. Subsequently, Finite-Element (FE) method is used to determine and verify the model parameters and to identify dominant dynamical regimes, natural modes and frequencies. The tank failure modes are identified and critical locations are identified. Mathematical relation is found between degrees-of-freedom (DOFs) motion and the mechanical stress applied in the tank critical section. This is the prior attempt to take under consideration large-amplitude nonlinear sloshing and tank structure elasticity effects for design, regulation definition and resistance analysis purposes. Both linear (tuned mass damper, TMD) and nonlinear (nonlinear energy sink, NES) passive energy absorbers contribution to the overall system mitigation is firstly examined, in terms of both stress reduction and time for vibration decay.

Keywords: nonlinear energy sink (NES), reduced-order modelling, liquid sloshing, vibration mitigation, vibro-impact dynamics

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Authors: Amanda Rithieli Pereira Dos Santos, Rute Quelvia De Faria, Álvaro De Oliveira Cardoso, Anderson Rodrigo Da Silva, Érica Leão Fernandes Araújo

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The study of the kinetics of drying has great importance for the mathematical modeling, allowing to know about the processes of transference of heat and mass between the products and to adjust dryers managing new technologies for these processes. The present work had the objective of studying the kinetics of drying of soybean seeds and adjusting different statistical models to the experimental data varying cultivar and temperature. Soybean seeds were pre-dried in a natural environment in order to reduce and homogenize the water content to the level of 14% (b.s.). Then, drying was carried out in a forced air circulation oven at controlled temperatures of 38, 43, 48, 53 and 58 ± 1 ° C, using two soybean cultivars, BRS 8780 and Sambaíba, until reaching a hygroscopic equilibrium. The experimental design was completely randomized in factorial 5 x 2 (temperature x cultivar) with 3 replicates. To the experimental data were adjusted eleven statistical models used to explain the drying process of agricultural products. Regression analysis was performed using the least squares Gauss-Newton algorithm to estimate the parameters. The degree of adjustment was evaluated from the analysis of the coefficient of determination (R²), the adjusted coefficient of determination (R² Aj.) And the standard error (S.E). The models that best represent the drying kinetics of soybean seeds are those of Midilli and Logarítmico.

Keywords: curve of drying seeds, Glycine max L., moisture ratio, statistical models

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Authors: Yeliz Ekinci, Melis Koyuncu

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Successful planning of solid waste management systems requires successful prediction of the amount of solid waste generated in an area. Waste management planning can protect the environment and human health, hence it is tremendously important for countries. The lack of information in waste generation can cause many environmental and health problems. Turkey is a country that plans to join European Union, hence, solid waste management is one of the most significant criteria that should be handled in order to be a part of this community. Solid waste management system requires a good forecast of solid waste generation. Thus, this study aims to forecast solid waste generation in Turkey. Artificial Neural Network and Linear Regression models will be used for this aim. Many models will be run and the best one will be selected based on some predetermined performance measures.

Keywords: forecast, solid waste generation, solid waste management, Turkey

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Authors: Ilya Simanovskii

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Nonlinear convective flows developed under the joint action of buoyant and thermo-capillary effects in a two-layer system with periodic boundary conditions on the lateral walls have been investigated. The influence of an interfacial heat release on oscillatory regimes has been studied. The computational regions with different lengths have been considered. It is shown that the development of oscillatory instability can lead to the appearance of different no steady flows.

Keywords: interface, instabilities, two-layer systems, bioinformatics, biomedicine

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Authors: Navab Karimi, Tohid Alizadeh

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An intelligent vision-based system was designed to measure the quality and purity of raisins. A machine vision setup was utilized to capture the images of bulk raisins in ranges of 5-50% mixed pure-impure berries. The textural features of bulk raisins were extracted using Grey-level Histograms, Co-occurrence Matrix, and Local Binary Pattern (a total of 108 features). Genetic Algorithm and neural network regression were used for selecting and ranking the best features (21 features). As a result, the GLCM features set was found to have the highest accuracy (92.4%) among the other sets. Followingly, multiple feature combinations of the previous stage were fed into the second regression (linear regression) to increase accuracy, wherein a combination of 16 features was found to be the optimum. Finally, a Support Vector Machine (SVM) classifier was used to differentiate the mixtures, producing the best efficiency and accuracy of 96.2% and 97.35%, respectively.

Keywords: sun-dried organic raisin, genetic algorithm, feature extraction, ann regression, linear regression, support vector machine, south azerbaijan.

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Authors: Serkan Aras, Emrah Gulay

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Combining various forecasting models is an important tool for researchers to attain more accurate forecasts. A great number of papers have shown that selecting single models as dissimilar models, or methods based on different information as possible leads to better forecasting performances. However, there is not a certain rule regarding the number of single models to be used in any combining methods. This study focuses on determining the optimal or near optimal number for single models with the help of statistical tests. An extensive experiment is carried out by utilizing some well-known time series data sets from diverse fields. Furthermore, many rival forecasting methods and some of the commonly used combining methods are employed. The obtained results indicate that some statistically significant performance differences can be found regarding the number of the single models in the combining methods under investigation.

Keywords: combined forecast, forecasting, M-competition, time series

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Authors: Jaan-Willem Simon, Bertram Stier, Brett Bednarcyk, Evan Pineda, Stefanie Reese

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Textile composites, in which the reinforcing fibers are woven or braided, have become very popular in numerous applications in aerospace, automotive, and maritime industry. These textile composites are advantageous due to their ease of manufacture, damage tolerance, and relatively low cost. However, physics-based modeling of the mechanical behavior of textile composites is challenging. Compared to their unidirectional counterparts, textile composites introduce additional geometric complexities, which cause significant local stress and strain concentrations. Since these internal concentrations are primary drivers of nonlinearity, damage, and failure within textile composites, they must be taken into account in order for the models to be predictive. The macro-scale approach to modeling textile-reinforced composites treats the whole composite as an effective, homogenized material. This approach is very computationally efficient, but it cannot be considered predictive beyond the elastic regime because the complex microstructural geometry is not considered. Further, this approach can, at best, offer a phenomenological treatment of nonlinear deformation and failure. In contrast, the mesoscale approach to modeling textile composites explicitly considers the internal geometry of the reinforcing tows, and thus, their interaction, and the effects of their curved paths can be modeled. The tows are treated as effective (homogenized) materials, requiring the use of anisotropic material models to capture their behavior. Finally, the micro-scale approach goes one level lower, modeling the individual filaments that constitute the tows. This paper will compare meso- and micro-scale approaches to modeling the deformation, damage, and failure of textile-reinforced polymer matrix composites. For the mesoscale approach, the woven composite architecture will be modeled using the finite element method, and an anisotropic damage model for the tows will be employed to capture the local nonlinear behavior. For the micro-scale, two different models will be used, the one being based on the finite element method, whereas the other one makes use of an embedded semi-analytical approach. The goal will be the comparison and evaluation of these approaches to modeling textile-reinforced composites in terms of accuracy, efficiency, and utility.

Keywords: multiscale modeling, continuum damage model, damage interaction, textile composites

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Authors: Omar Dib, Rita Yaacoub, Luc Eveleigh, Nathalie Locquet, Hussein Dib, Ali Bassal, Christophe B. Y. Cordella

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The potential of front-face fluorescence coupled with chemometric techniques, namely parallel factor analysis (PARAFAC) and multiple linear regression (MLR) as a rapid analysis tool to characterize Lebanese virgin olive oils was investigated. Fluorescence fingerprints were acquired directly on 102 Lebanese virgin olive oil samples in the range of 280-540 nm in excitation and 280-700 nm in emission. A PARAFAC model with seven components was considered optimal with a residual of 99.64% and core consistency value of 78.65. The model revealed seven main fluorescence profiles in olive oil and was mainly associated with tocopherols, polyphenols, chlorophyllic compounds and oxidation/hydrolysis products. 23 MLR regression models based on PARAFAC scores were generated, the majority of which showed a good correlation coefficient (R > 0.7 for 12 predicted variables), thus satisfactory prediction performances. Acid values, peroxide values, and Delta K had the models with the highest predictions, with R values of 0.89, 0.84 and 0.81 respectively. Among fatty acids, linoleic and oleic acids were also highly predicted with R values of 0.8 and 0.76, respectively. Factors contributing to the model's construction were related to common fluorophores found in olive oil, mainly chlorophyll, polyphenols, and oxidation products. This study demonstrates the interest of front-face fluorescence as a promising tool for quality control of Lebanese virgin olive oils.

Keywords: front-face fluorescence, Lebanese virgin olive oils, multiple Linear regressions, PARAFAC analysis

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Authors: Shan-Hong Ying, Ying-Fang Wang

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A surrogate approach was deployed for assessing exposures of multiple chemicals at the selected working area of coating processes and applied to assess the exposure concentration of similar exposed groups using the same chemicals but different formula ratios. For the selected area, 6 to 12 portable photoionization detector (PID) were placed uniformly in its workplace to measure its total VOCs concentrations (CT-VOCs) for 6 randomly selected workshifts. Simultaneously, one sampling strain was placed beside one of these portable PIDs, and the collected air sample was analyzed for individual concentration (CVOCi) of 5 VOCs (xylene, butanone, toluene, butyl acetate, and dimethylformamide). Predictive models were established by relating the CT-VOCs to CVOCi of each individual compound via simple regression analysis. The established predictive models were employed to predict each CVOCi based on the measured CT-VOC for each the similar working area using the same portable PID. Results show that predictive models obtained from simple linear regression analyses were found with an R2 = 0.83~0.99 indicating that CT-VOCs were adequate for predicting CVOCi. In order to verify the validity of the exposure prediction model, the sampling analysis of the above chemical substances was further carried out and the correlation between the measured value (Cm) and the predicted value (Cp) was analyzed. It was found that there is a good correction between the predicted value and measured value of each measured chemical substance (R2=0.83~0.98). Therefore, the surrogate approach could be assessed the exposure concentration of similar exposed groups using the same chemicals but different formula ratios. However, it is recommended to establish the prediction model between the chemical substances belonging to each coater and the direct-reading PID, which is more representative of reality exposure situation and more accurately to estimate the long-term exposure concentration of operators.

Keywords: exposure assessment, exposure prediction model, surrogate approach, TVOC

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Authors: Luh Eka Suryani, Purhadi

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Poisson regression is a non-linear regression model with response variable in the form of count data that follows Poisson distribution. Modeling for a pair of count data that show high correlation can be analyzed by Poisson Bivariate Regression. Data, the number of infant mortality and maternal mortality, are count data that can be analyzed by Poisson Bivariate Regression. The Poisson regression assumption is an equidispersion where the mean and variance values are equal. However, the actual count data has a variance value which can be greater or less than the mean value (overdispersion and underdispersion). Violations of this assumption can be overcome by applying Generalized Poisson Regression. Characteristics of each regency can affect the number of cases occurred. This issue can be overcome by spatial analysis called geographically weighted regression. This study analyzes the number of infant mortality and maternal mortality based on conditions in East Java in 2016 using Geographically Weighted Bivariate Generalized Poisson Regression (GWBGPR) method. Modeling is done with adaptive bisquare Kernel weighting which produces 3 regency groups based on infant mortality rate and 5 regency groups based on maternal mortality rate. Variables that significantly influence the number of infant and maternal mortality are the percentages of pregnant women visit health workers at least 4 times during pregnancy, pregnant women get Fe3 tablets, obstetric complication handled, clean household and healthy behavior, and married women with the first marriage age under 18 years.

Keywords: adaptive bisquare kernel, GWBGPR, infant mortality, maternal mortality, overdispersion

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Authors: N. Kaewpraek, W. Assawinchaichote

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This paper considers an H_∞ TS fuzzy state-derivative feedback controller for a class of nonlinear dynamical systems. A Takagi-Sugeno (TS) fuzzy model is used to approximate a class of nonlinear dynamical systems. Then, based on a linear matrix inequality (LMI) approach, we design an H_∞ TS fuzzy state-derivative feedback control law which guarantees L₂-gain of the mapping from the exogenous input noise to the regulated output to be less or equal to a prescribed value. We derive a sufficient condition such that the system with the fuzzy controller is asymptotically stable and H_∞ performance is satisfied. Finally, we provide and simulate a numerical example is provided to illustrate the stability and the effectiveness of the proposed controller.

Keywords: h-infinity fuzzy control, an LMI approach, Takagi-Sugano (TS) fuzzy system, the photovoltaic systems

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Authors: Sheena K. J., Jyoti Badge, Sayed Mohammed Zeeshan

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A Comparative Study of Exponential and Logistic Population Growth Models in India India is the second most populous city in the world, just behind China, and is going to be in the first place by next year. The Indian population has remarkably at higher rate than the other countries from the past 20 years. There were many scientists and demographers who has formulated various models of population growth in order to study and predict the future population. Some of the models are Fibonacci population growth model, Exponential growth model, Logistic growth model, Lotka-Volterra model, etc. These models have been effective in the past to an extent in predicting the population. However, it is essential to have a detailed comparative study between the population models to come out with a more accurate one. Having said that, this research study helps to analyze and compare the two population models under consideration - exponential and logistic growth models, thereby identifying the most effective one. Using the census data of 2011, the approximate population for 2016 to 2031 are calculated for 20 Indian states using both the models, compared and recorded the data with the actual population. On comparing the results of both models, it is found that logistic population model is more accurate than the exponential model, and using this model, we can predict the future population in a more effective way. This will give an insight to the researchers about the effective models of population and how effective these population models are in predicting the future population.

Keywords: population growth, population models, exponential model, logistic model, fibonacci model, lotka-volterra model, future population prediction, demographers

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Authors: Temur Chilachava

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In work the new nonlinear mathematical model describing assimilation of the people (population) with some less widespread language by two states with two various widespread languages, taking into account demographic factor is offered. In model three subjects are considered: the population and government institutions with the widespread first language, influencing by means of state and administrative resources on the third population with some less widespread language for the purpose of their assimilation; the population and government institutions with the widespread second language, influencing by means of state and administrative resources on the third population with some less widespread language for the purpose of their assimilation; the third population (probably small state formation, an autonomy), exposed to bilateral assimilation from two rather powerful states. Earlier by us it was shown that in case of zero demographic factor of all three subjects, the population with less widespread language completely assimilates the states with two various widespread languages, and the result of assimilation (redistribution of the assimilated population) is connected with initial quantities, technological and economic capabilities of the assimilating states. In considered model taking into account demographic factor natural decrease in the population of the assimilating states and a natural increase of the population which has undergone bilateral assimilation is supposed. At some ratios between coefficients of natural change of the population of the assimilating states, and also assimilation coefficients, for nonlinear system of three differential equations are received the two first integral. Cases of two powerful states assimilating the population of small state formation (autonomy), with different number of the population, both with identical and with various economic and technological capabilities are considered. It is shown that in the first case the problem is actually reduced to nonlinear system of two differential equations describing the classical model "predator - the victim", thus, naturally a role of the victim plays the population which has undergone assimilation, and a predator role the population of one of the assimilating states. The population of the second assimilating state in the first case changes in proportion (the coefficient of proportionality is equal to the relation of the population of assimilators in an initial time point) to the population of the first assimilator. In the second case the problem is actually reduced to nonlinear system of two differential equations describing type model "a predator – the victim", with the closed integrated curves on the phase plane. In both cases there is no full assimilation of the population to less widespread language. Intervals of change of number of the population of all three objects of model are found. The considered mathematical models which in some approach can model real situations, with the real assimilating countries and the state formations (an autonomy or formation with the unrecognized status), undergone to bilateral assimilation, show that for them the only possibility to avoid from assimilation is the natural demographic increase in population and hope for natural decrease in the population of the assimilating states.

Keywords: nonlinear mathematical model, bilateral assimilation, demographic factor, first integrals, result of assimilation, intervals of change of number of the population

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Authors: Ahmad Forouzantabar, Mohammad Azadi, Alireza Alesaadi

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This paper describes a sliding mode controller for autonomous underwater vehicles (AUVs). The dynamic of AUV model is highly nonlinear because of many factors, such as hydrodynamic drag, damping, and lift forces, Coriolis and centripetal forces, gravity and buoyancy forces, as well as forces from thruster. To address these difficulties, a nonlinear sliding mode controller is designed to approximate the nonlinear dynamics of AUV and improve trajectory tracking. Moreover, the proposed controller can profoundly attenuate the effects of uncertainties and external disturbances in the closed-loop system. Using the Lyapunov theory the boundedness of AUV tracking errors and the stability of the proposed control system are also guaranteed. Numerical simulation studies of an AUV are included to illustrate the effectiveness of the presented approach.

Keywords: lyapunov stability, autonomous underwater vehicle, sliding mode controller, electronics engineering

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Authors: Lin-Han Chiang Hsieh, Hsiao-Yi Lin

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This study aims to determine the impact of the disclosure of flood potential map on housing prices. The disclosure is supposed to mitigate the market failure by reducing information asymmetry. On the other hand, opponents argue that the official disclosure of simulated results will only create unnecessary disturbances on the housing market. This study identifies the impact of the disclosure of the flood potential map by comparing the hedonic price of flood potential before and after the disclosure. The flood potential map used in this study is published by Taipei municipal government in 2015, which is a result of a comprehensive simulation based on geographical, hydrological, and meteorological factors. The residential property sales data of 2013 to 2016 is used in this study, which is collected from the actual sales price registration system by the Department of Land Administration (DLA). The result shows that the impact of flood potential on residential real estate market is statistically significant both before and after the disclosure. But the trend is clearer after the disclosure, suggesting that the disclosure does have an impact on the market. Also, the result shows that the impact of flood potential differs by the severity and frequency of precipitation. The negative impact for a relatively mild, high frequency flood potential is stronger than that for a heavy, low possibility flood potential. The result indicates that home buyers are of more concern to the frequency, than the intensity of flood. Another contribution of this study is in the methodological perspective. The classic hedonic price analysis with OLS regression suffers from two spatial problems: the endogeneity problem caused by omitted spatial-related variables, and the heterogeneity concern to the presumption that regression coefficients are spatially constant. These two problems are seldom considered in a single model. This study tries to deal with the endogeneity and heterogeneity problem together by combining the spatial fixed-effect model and geographically weighted regression (GWR). A series of literature indicates that the hedonic price of certain environmental assets varies spatially by applying GWR. Since the endogeneity problem is usually not considered in typical GWR models, it is arguable that the omitted spatial-related variables might bias the result of GWR models. By combing the spatial fixed-effect model and GWR, this study concludes that the effect of flood potential map is highly sensitive by location, even after controlling for the spatial autocorrelation at the same time. The main policy application of this result is that it is improper to determine the potential benefit of flood prevention policy by simply multiplying the hedonic price of flood risk by the number of houses. The effect of flood prevention might vary dramatically by location.

Keywords: flood potential, hedonic price analysis, endogeneity, heterogeneity, geographically-weighted regression

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Authors: Subha D. Puthankattil, Paul K. Joseph

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Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy.

Keywords: EEG, depression, wavelet entropy, approximate entropy, relative wavelet energy, multiresolution decomposition

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Authors: V. D. Thi, M. Li, M. Khelifa, M. El Ganaoui, Y. Rogaume

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This paper presents a two-dimensional model to study the heat and moisture transfer through porous building materials. Dynamic and static coupled models of heat and moisture transfer in porous material under low temperature are presented and the coupled models together with variable initial and boundary conditions have been considered in an analytical way and using the finite element method. The resulting coupled model is converted to two nonlinear partial differential equations, which is then numerically solved by an implicit iterative scheme. The numerical results of temperature and moisture potential changes are compared with the experimental measurements available in the literature. Predicted results demonstrate validation of the theoretical model and effectiveness of the developed numerical algorithms. It is expected to provide useful information for the porous building material design based on heat and moisture transfer model.

Keywords: finite element method, heat transfer, moisture transfer, porous materials, wood

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Authors: S. Ghorbani, N. I. Polushin

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In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value.

Keywords: cutting condition, surface roughness, decision tree, CART algorithm

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Authors: Anton S. Perin, Vladimir M. Shandarov

Abstract:

Compensation for the nonlinear diffraction of narrow laser beams with wavelength of 532 and the formation of photonic waveguides and waveguide circuits due to the contribution of pyroelectric effect to the nonlinear response of lithium niobate crystal have been experimentally demonstrated. Complete compensation for the linear and nonlinear diffraction broadening of light beams is obtained upon uniform heating of an undoped sample from room temperature to 55 degrees Celsius. An analysis of the light-field distribution patterns and the corresponding intensity distribution profiles allowed us to estimate the spacing for the channel waveguides. The observed behavior of bright soliton beams may be caused by their coherent interaction, which manifests itself in repulsion for anti-phase light fields and in attraction for in-phase light fields. The experimental results of this study showed a fundamental possibility of forming optically complex waveguide structures in lithium niobate crystals with pyroelectric mechanism of nonlinear response. The topology of these structures is determined by the light field distribution on the input face of crystalline sample. The optical induction of channel waveguide elements by interacting spatial solitons makes it possible to design optical systems with a more complex topology and a possibility of their dynamic reconfiguration.

Keywords: self-action, soliton, lithium niobate, piroliton, photorefractive effect, pyroelectric effect

Procedia PDF Downloads 151

Authors: Shilpa Khobragade, Carlos Da Silva Granja, Niklas Sandström, Igor Efimov, Victor P. Ostanin, Wouter van der Wijngaart, David Klenerman, Sourav K. Ghosh

Abstract:

Rapid, label-free and direct detection of pathogenic bacteria is critical for the prevention of disease outbreaks. This paper for the first time attempts to probe the nonlinear acoustic response of quartz crystal resonator (QCR) functionalized with specific DNA aptamers for direct detection and quantification of viable E. coli KCTC 2571 bacteria. DNA aptamers were immobilized through biotin and streptavidin conjugation, onto the gold surface of QCR to capture the target bacteria and the detection was accomplished by shift in amplitude of the peak 3f signal (3 times the drive frequency) upon binding, when driven near fundamental resonance frequency. The developed nonlinear acoustic aptasensor system demonstrated better reliability than conventional resonance frequency shift and energy dissipation monitoring that were recorded simultaneously. This sensing system could directly detect 10⁽⁵⁾ cells/mL target bacteria within 30 min or less and had high specificity towards E. coli KCTC 2571 bacteria as compared to the same concentration of S.typhi bacteria. Aptasensor response was observed for the bacterial suspensions ranging from 10⁽⁵⁾-10⁽⁸⁾ cells/mL. Conclusively, this nonlinear acoustic aptasensor is simple to use, gives real-time output, cost-effective and has the potential for rapid, specific, label-free direction detection of bacteria.

Keywords: acoustic, aptasensor, detection, nonlinear

Procedia PDF Downloads 550

Authors: Donatello Cardone

Abstract:

Bilinear hysteresis models are usually used to describe the cyclic behavior of high damping rubber bearings. However, they neglect a number of phenomena (such as the interaction between axial load and shear force, buckling and post-buckling behavior, cavitation, scragging effects, etc.) that can significantly influence the dynamic behavior of such isolation devices. In this work, an advanced hysteresis model is examined and properly calibrated using consolidated procedures. Results of preliminary numerical analyses, performed in OpenSees, are shown and compared with the results of experimental tests on high damping rubber bearings and simulation analyses using alternative nonlinear models. The findings of this study can provide an useful tool for the accurate evaluation of the seismic response of structures with rubber-based isolation systems.

Keywords: seismic isolation, high damping rubber bearings, numerical modeling, axial-shear force interaction

Procedia PDF Downloads 113

Authors: Ekele Alih, Enejo Jalija

Abstract:

Female Genital Mutilation (FGM) is made up of three types namely: Clitoridectomy, Excision and Infibulation. In this study, we examine the factors responsible for FGM in order to identify the causality variables in a logistic regression approach. From the result of the survey conducted by the Public Health Division, Nigeria Institute of Medical Research, Yaba, Lagos State, the tau statistic, τ was used to screen 9 factors that causes FGM in order to select few of the predictors before multiple regression equation is obtained. The need for this may be that the sample size may not be able to sustain having a regression with all the predictors or to avoid multi-collinearity. A total of 300 respondents, comprising 150 adult males and 150 adult females were selected for the household survey based on the multi-stage sampling procedure. The tau statistic,

Keywords: female genital mutilation, logistic regression, tau statistic, African society

Procedia PDF Downloads 241