Search results for: linear and polynomial model

Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

Abstract:

Without a doubt, soil shear strength is the most important property of the soil. The majority of fatal and catastrophic geological accidents are related to shear strength failure of the soil. Therefore, its prediction is a matter of high importance. However, acquiring the shear strength is usually a cumbersome task that might need complicated laboratory testing. Therefore, prediction of it based on common and easy to get soil properties can simplify the projects substantially. In this paper, A hybrid model based on the classification and regression tree algorithm and logistic regression is proposed where each leaf of the tree is an independent regression model. A database of 189 points for clay soil, including Moisture content, liquid limit, plastic limit, clay content, and shear strength, is collected. The performance of the developed model compared to the existing models and equations using root mean squared error and coefficient of correlation.

Keywords: model tree, CART, logistic regression, soil shear strength

Procedia PDF Downloads 180

Authors: H. Namazi, H. T. N. Kuan

Abstract:

Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to visual stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to visual stimuli but provide us with very good recommendations for clinical purposes.

Keywords: visual stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

Procedia PDF Downloads 544

Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

Abstract:

In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: deep learning, convolutional neural network, LSTM, housing prediction

Procedia PDF Downloads 294

Authors: Hadia Abdel Aziz, Raghda El Ebrashi

Abstract:

Business models are shaped by their design space or the environment they are designed to be implemented in. The rapidly changing economic, technological, political, regulatory and market external environment severely affects business logic. This is particularly true for social enterprises whose core mission is to transform their environments, and thus, their whole business logic revolves around the interchange between the enterprise and the environment. The context in which social business operates imposes different business design constraints while at the same time, open up new design opportunities. It is also affected to a great extent by the impact that successful enterprises generate; a continuous loop of interaction that needs to be managed through a dynamic capability in order to generate a lasting powerful impact. This conceptual research synthesizes and analyzes literature on social enterprise, social enterprise business models, business model innovation, business model design, and the open system view theory to propose a new business model design process for social enterprises that takes into account the critical role of environmental factors. This process would help the social enterprise develop a dynamic capability that ensures the alignment of its business model to its environmental context, thus, maximizing its probability of success.

Keywords: social enterprise, business model, business model design, business model environment

Procedia PDF Downloads 354

Authors: Abdel Hadi Ebraheim

Abstract:

This paper introduces a new extension of the Inverse Pareto distribution in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure data. The statistical properties of the new model are discussed. Several methods are used to estimate the parameters involved. Explicit expressions are derived for different types of moments of value in reliability analysis are obtained. Besides, the order statistics of samples from the new proposed model have been studied. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study.

Keywords: pareto distribution, marshal-Olkin, reliability, hazard functions, moments, estimation

Procedia PDF Downloads 74

Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

Abstract:

Due to its porous nature, karst terrains – geomorphologically developed from dissolved formations, is vulnerable to water shortage and deteriorated water quality. Therefore, a solid comprehension on sub-surface flow of karst landscape is essential to assess the long-term availability of groundwater resources. In this paper, a single-continuum model using a finite difference model, MODLFOW, was constructed to represent an unconfined carbonate aquifer in a tropical karst island of Rote in Indonesia. The model, spatially discretized in 20 x 20 m grid cells, was calibrated and validated using available groundwater level and atmospheric variables. In the calibration and validation steps, Parameter Estimation (PEST) and geostatistical pilot point methods were employed to estimate hydraulic conductivity and specific yield values. The results show that the model is able to represent the sub-surface flow indicated by good model performances both in calibration and validation steps. The final model can be used as a robust representation of the system for future study on climate and land use scenarios.

Keywords: carbonate aquifer, karst, sub-surface flow, groundwater model

Procedia PDF Downloads 141

Authors: Irene Carter, Roy Hanes, Judy MacDonald

Abstract:

Considering that disability is universal and people with disabilities are part of all societies; that there is a connection between the disabled individual and the societal; and that it is society and social arrangements that disable people with impairments, contemporary disability discourse emphasizes the social model of disability to counter medical and rehabilitative models of disability. However, the social model does not go far enough in addressing the issues of oppression and inclusion. The authors indicate that the social model does not specifically or adequately denote the oppression of persons with disabilities, which is a central component of progressive social work practice with people with disabilities. The social model of disability does not go far enough in deconstructing disability and offering social workers, as well as people with disabilities a way of moving forward in terms of practice anchored in individual, familial and societal change. The social model of disability is expanded by incorporating principles of anti-oppression social work practice. Although the contextual analysis of the social model of disability is an important component there remains a need for social workers to provide service to individuals and their families, which will be illustrated through anti-oppressive practice (AOP). By applying an anti-oppressive model of practice to the above definitions, the authors not only deconstruct disability paradigms but illustrate how AOP offers a framework for social workers to engage with people with disabilities at the individual, familial and community levels of practice, promoting an emancipatory focus in working with people with disabilities. An anti- social- oppression social work model of disability connects the day-to-day hardships of people with disabilities to the direct consequence of oppression in the form of ableism. AOP theory finds many of its basic concepts within social-oppression theory and the social model of disability. It is often the case that practitioners, including social workers and psychologists, define people with disabilities’ as having or being a problem with the focus placed upon adjustment and coping. A case example will be used to illustrate how an AOP paradigm offers social work a more comprehensive and critical analysis and practice model for social work practice with and for people with disabilities than the traditional medical model, rehabilitative and social model approaches.

Keywords: anti-oppressive practice, disability, people with disabilities, social model of disability

Procedia PDF Downloads 1048

Authors: Saad M. Darwish

Abstract:

Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However, these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: software quality, quality assurance, software certification model, software assessment

Procedia PDF Downloads 511

Authors: Gyoutae Park, Seungho Han, Byungduk Kim, Youngdo Jo, Yongsop Shim, Yeonjae Lee, Sangguk Ahn, Hiesik Kim, Jungil Park

Abstract:

In this paper, we presented not only development technology of an explosion proof type and portable combustible gas leak detector but also algorithm to improve accuracy for measuring gas concentrations. The presented techniques are to apply the flame-proof enclosure and intrinsic safe explosion proof to an infrared gas leak detector at first in Korea and to improve accuracy using linearization recursion equation and Lagrange interpolation polynomial. Together, we tested sensor characteristics and calibrated suitable input gases and output voltages. Then, we advanced the performances of combustible gaseous detectors through reflecting demands of gas safety management fields. To check performances of two company's detectors, we achieved the measurement tests with eight standard gases made by Korea Gas Safety Corporation. We demonstrated our instruments better in detecting accuracy other than detectors through experimental results.

Keywords: accuracy improvement, IR gas sensor, gas leak, detector

Procedia PDF Downloads 382

Authors: Hui Wei, Zheng Dong

Abstract:

Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

Procedia PDF Downloads 531

Authors: Abdul-Monim Batiha, Manar AlAzzam, Mohammed ALBashtawy, Loai Tawalbeh, Ahmad Tubaishat, Fadwa N. Alhalaiqa

Abstract:

Background: Obesity is the major modifiable risk factor for many chronic illnesses especially high blood pressure. Objectives: To evaluate the relationship between anthropometric indices and high blood pressure, and which one was most strongly correlated with high blood pressure in Jordanian population. Methods: A cross-sectional study was conducted with a total 622 students and workers from three Jordanian universities. Results: Nearly half of the participant are overweight (34.7%) and obese (15.4%) and hypertension was detected among 138 (22.2%) of the participants. Linear correlation was significant (p<0.01) between both systolic blood pressure and diastolic blood pressure for all anthropometric indices, except for A body shape index and diastolic blood pressure was significant at p< 0.05. Stepwise multiple linear regression analysis was used to assess the influence of age and anthropometric measurements. Conclusions: The waist circumference was the only independent predictor of hypertension, showing that this simple measurement may be an importance marker of high blood pressure in Jordanian population.

Keywords: anthropometric indices, Jordan, blood pressure, cross-sectional study, obesity, hypertension, waist circumference

Procedia PDF Downloads 280

Authors: Myungjin Lee, Daegun Han, Jongsung Kim, Soojun Kim, Hung Soo Kim

Abstract:

Recently, the localized heavy rainfall and typhoons are frequently occurred due to the climate change and the damage is becoming bigger. Therefore, we may need a more accurate prediction of the rainfall and runoff. However, the gauge rainfall has the limited accuracy in space. Radar rainfall is better than gauge rainfall for the explanation of the spatial variability of rainfall but it is mostly underestimated with the uncertainty involved. Therefore, the ensemble of radar rainfall was simulated using error structure to overcome the uncertainty and gauge rainfall. The simulated ensemble was used as the input data of the rainfall-runoff models for obtaining the ensemble of runoff hydrographs. The previous studies discussed about the accuracy of the rainfall-runoff model. Even if the same input data such as rainfall is used for the runoff analysis using the models in the same basin, the models can have different results because of the uncertainty involved in the models. Therefore, we used two models of the SSARR model which is the lumped model, and the Vflo model which is a distributed model and tried to simulate the optimum runoff considering the uncertainty of each rainfall-runoff model. The study basin is located in Han river basin and we obtained one integrated runoff hydrograph which is an optimum runoff hydrograph using the blending methods such as Multi-Model Super Ensemble (MMSE), Simple Model Average (SMA), Mean Square Error (MSE). From this study, we could confirm the accuracy of rainfall and rainfall-runoff model using ensemble scenario and various rainfall-runoff model and we can use this result to study flood control measure due to climate change. Acknowledgements: This work is supported by the Korea Agency for Infrastructure Technology Advancement(KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 18AWMP-B083066-05).

Keywords: radar rainfall ensemble, rainfall-runoff models, blending method, optimum runoff hydrograph

Procedia PDF Downloads 264

Authors: Arturo Galván, Jatziri Y. Moreno-Martínez, Israel Enrique Herrera Díaz, José Ramón Gasca Tirado

Abstract:

In recent years, one of the methods most used for the construction of tunnels in soft soil is the shield-driven tunneling. The advantage of this construction technique is that it allows excavating the tunnel while at the same time a primary lining is placed, which consists of precast segments. There are joints between segments, also called longitudinal joints, and joints between rings (called as circumferential joints). This is the reason because of this type of constructions cannot be considered as a continuous structure. The effect of these joints influences in the rigidity of the segmental lining and therefore in its structural response. A parametric study was performed to take into account the effect of different parameters in the structural response of typical segmental tunnels built in soft soil by using non-linear numerical models based on Finite Element Method by means of the software package ANSYS v. 11.0. In the first part of this study, two types of numerical models were performed. In the first one, the segments were modeled by using beam elements based on Timoshenko beam theory whilst the segment joints were modeled by using inelastic rotational springs considering the constitutive moment-rotation relation proposed by Gladwell. In this way, the mechanical behavior of longitudinal joints was simulated. On the other hand for simulating the mechanical behavior of circumferential joints elastic springs were considered. As well as, the stability given by the soil was modeled by means of elastic-linear springs. In the second type of models, the segments were modeled by means of three-dimensional solid elements and the joints with contact elements. In these models, the zone of the joints is modeled as a discontinuous (increasing the computational effort) therefore a discrete model is obtained. With these contact elements the mechanical behavior of joints is simulated considering that when the joint is closed, there is transmission of compressive and shear stresses but not of tensile stresses and when the joint is opened, there is no transmission of stresses. This type of models can detect changes in the geometry because of the relative movement of the elements that form the joints. A comparison between the numerical results with two types of models was carried out. In this way, the hypothesis considered in the simplified models were validated. In addition, the numerical models were calibrated with (Lab-based) experimental results obtained from the literature of a typical tunnel built in Europe. In the second part of this work, a parametric study was performed by using the simplified models due to less used computational effort compared to complex models. In the parametric study, the effect of material properties, the geometry of the tunnel, the arrangement of the longitudinal joints and the coupling of the rings were studied. Finally, it was concluded that the mechanical behavior of segment and ring joints and the arrangement of the segment joints affect the global behavior of the lining. As well as, the effect of the coupling between rings modifies the structural capacity of the lining.

Keywords: numerical models, parametric study, segmental tunnels, structural response

Procedia PDF Downloads 220

Authors: Idrissa Kayijuka

Abstract:

The logistic regression and Cox regression models (proportional hazard model) at present are being employed in the analysis of prospective epidemiologic research looking into risk factors in their application on chronic diseases. However, a theoretical relationship between the two models has been studied. By definition, Cox regression model also called Cox proportional hazard model is a procedure that is used in modeling data regarding time leading up to an event where censored cases exist. Whereas the Logistic regression model is mostly applicable in cases where the independent variables consist of numerical as well as nominal values while the resultant variable is binary (dichotomous). Arguments and findings of many researchers focused on the overview of Cox and Logistic regression models and their different applications in different areas. In this work, the analysis is done on secondary data whose source is SPSS exercise data on BREAST CANCER with a sample size of 1121 women where the main objective is to show the application difference between Cox regression model and logistic regression model based on factors that cause women to die due to breast cancer. Thus we did some analysis manually i.e. on lymph nodes status, and SPSS software helped to analyze the mentioned data. This study found out that there is an application difference between Cox and Logistic regression models which is Cox regression model is used if one wishes to analyze data which also include the follow-up time whereas Logistic regression model analyzes data without follow-up-time. Also, they have measurements of association which is different: hazard ratio and odds ratio for Cox and logistic regression models respectively. A similarity between the two models is that they are both applicable in the prediction of the upshot of a categorical variable i.e. a variable that can accommodate only a restricted number of categories. In conclusion, Cox regression model differs from logistic regression by assessing a rate instead of proportion. The two models can be applied in many other researches since they are suitable methods for analyzing data but the more recommended is the Cox, regression model.

Keywords: logistic regression model, Cox regression model, survival analysis, hazard ratio

Procedia PDF Downloads 440

Authors: R. Sabre, W. Horrigue, J. C. Simon

Abstract:

This paper is interested in two difficulties encountered in practice when observing a continuous time process. The first is that we cannot observe a process over a time interval; we only take discrete observations. The second is the process frequently observed with a constant additive error. It is important to give an estimator of the spectral density of such a process taking into account the additive observation error and the choice of the discrete observation times. In this work, we propose an estimator based on the spectral smoothing of the periodogram by the polynomial Jackson kernel reducing the additive error. In order to solve the aliasing phenomenon, this estimator is constructed from observations taken at well-chosen times so as to reduce the estimator to the field where the spectral density is not zero. We show that the proposed estimator is asymptotically unbiased and consistent. Thus we obtain an estimate solving the two difficulties concerning the choice of the instants of observations of a continuous time process and the observations affected by a constant error.

Keywords: spectral density, stable processes, aliasing, periodogram

Procedia PDF Downloads 126

Authors: Yousef Al-Qaryouti, Besan Alagawani

Abstract:

The main concern of this study is to evaluate the effect of adding horizontal steel bracing system to ordinary moment resisting steel frames subjected to wind load. Similar frames without bracing systems are also to be compared. A general analytical study was carried out to obtain the influence of such system in resisting wind load. Linear static analysis has been carried out using ETABS software by applying fixed wind load defined according to ASCE7-10 for three-, six-, nine-, and twelve-story ordinary moment steel frame buildings including and not including horizontal steel bracing system. The results showed that the lateral drift due to wind load decreased by adding horizontal bracing system. Also, the results show that effect of such system is more efficient to low-rise buildings.

Keywords: horizontal bracing system, steel moment frames, wind load resisting system, linear static analysis

Procedia PDF Downloads 278

Authors: S. O. Oyamakin, A. U. Chukwu

Abstract:

Richard's growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richard's growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richard's growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richard's nonlinear growth models better than the classical Richard's growth model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, Richard's, stochastic

Procedia PDF Downloads 468

Authors: Tengqin Han

Abstract:

Delinquency has been a crucial factor in economics throughout the years. Commonly seen in credit card and mortgage, it played one of the crucial roles in causing the most recent financial crisis in 2008. In each case, a delinquency is a sign of the loaner being unable to pay off the debt, and thus may cause a lost of property in the end. Individually, one case of delinquency seems unimportant compared to the entire credit system. China, as an emerging economic entity, the national strength and economic strength has grown rapidly, and the gross domestic product (GDP) growth rate has remained as high as 8% in the past decades. However, potential risks exist behind the appearance of prosperity. Among the risks, the credit system is the most significant one. Due to long term and a large amount of balance of the mortgage, it is critical to monitor the risk during the performance period. In this project, about 300,000 mortgage account data are analyzed in order to develop a predictive model to predict the probability of delinquency. Through univariate analysis, the data is cleaned up, and through bivariate analysis, the variables with strong predictive power are detected. The project is divided into two parts. In the first part, the analysis data of 2005 are split into 2 parts, 60% for model development, and 40% for in-time model validation. The KS of model development is 31, and the KS for in-time validation is 31, indicating the model is stable. In addition, the model is further validation by out-of-time validation, which uses 40% of 2006 data, and KS is 33. This indicates the model is still stable and robust. In the second part, the model is improved by the addition of macroeconomic economic indexes, including GDP, consumer price index, unemployment rate, inflation rate, etc. The data of 2005 to 2010 is used for model development and validation. Compared with the base model (without microeconomic variables), KS is increased from 41 to 44, indicating that the macroeconomic variables can be used to improve the separation power of the model, and make the prediction more accurate.

Keywords: delinquency, mortgage, model development, model validation

Procedia PDF Downloads 214

Authors: Edwin Calderon-Mendoza, Patrick Schweitzer, Serge Weber

Abstract:

Series arc faults appear frequently and unpredictably in low voltage distribution systems. Many methods have been developed to detect this type of faults and commercial protection systems such AFCI (arc fault circuit interrupter) have been used successfully in electrical networks to prevent damage and catastrophic incidents like fires. However, these devices do not allow series arc faults to be located on the line in operating mode. This paper presents a location algorithm for series arc fault in a low-voltage indoor power line in an AC 230 V-50Hz home network. The method is validated through simulations using the MATLAB software. The fault location method uses electrical parameters (resistance, inductance, capacitance, and conductance) of a 49 m indoor power line. The mathematical model of a series arc fault is based on the analysis of the V-I characteristics of the arc and consists basically of two antiparallel diodes and DC voltage sources. In a first step, the arc fault model is inserted at some different positions across the line which is modeled using lumped parameters. At both ends of the line, currents and voltages are recorded for each arc fault generation at different distances. In the second step, a fault map trace is created by using signature coefficients obtained from Kirchhoff equations which allow a virtual decoupling of the line’s mutual capacitance. Each signature coefficient obtained from the subtraction of estimated currents is calculated taking into account the Discrete Fast Fourier Transform of currents and voltages and also the fault distance value. These parameters are then substituted into Kirchhoff equations. In a third step, the same procedure described previously to calculate signature coefficients is employed but this time by considering hypothetical fault distances where the fault can appear. In this step the fault distance is unknown. The iterative calculus from Kirchhoff equations considering stepped variations of the fault distance entails the obtaining of a curve with a linear trend. Finally, the fault distance location is estimated at the intersection of two curves obtained in steps 2 and 3. The series arc fault model is validated by comparing current registered from simulation with real recorded currents. The model of the complete circuit is obtained for a 49m line with a resistive load. Also, 11 different arc fault positions are considered for the map trace generation. By carrying out the complete simulation, the performance of the method and the perspectives of the work will be presented.

Keywords: indoor power line, fault location, fault map trace, series arc fault

Procedia PDF Downloads 127

Authors: Zyad Elkhadir, Khalid Chougdali, Mohammed Benattou

Abstract:

Most of the existing intrusion detection systems works on quantitative network traffic data with many irrelevant and redundant features, which makes detection process more time’s consuming and inaccurate. A several feature extraction methods, such as linear discriminant analysis (LDA), have been proposed. However, LDA suffers from the small sample size (SSS) problem which occurs when the number of the training samples is small compared with the samples dimension. Hence, classical LDA cannot be applied directly for high dimensional data such as network traffic data. In this paper, we propose two solutions to solve SSS problem for LDA and apply them to a network IDS. The first method, reduce the original dimension data using principal component analysis (PCA) and then apply LDA. In the second solution, we propose to use the pseudo inverse to avoid singularity of within-class scatter matrix due to SSS problem. After that, the KNN algorithm is used for classification process. We have chosen two known datasets KDDcup99 and NSLKDD for testing the proposed approaches. Results showed that the classification accuracy of (PCA+LDA) method outperforms clearly the pseudo inverse LDA method when we have large training data.

Keywords: LDA, Pseudoinverse, PCA, IDS, NSL-KDD, KDDcup99

Procedia PDF Downloads 217

Authors: M. Khaing, A. V. Tkacheva

Abstract:

The work is devoted to solving the problem of temperature stresses, caused by the heating point of the round plate. The plate is made of elastoplastic material, so the Prandtl-Reis model is used. A piecewise-linear condition of the Ishlinsky-Ivlev flow is taken as the loading surface, in which the yield stress depends on the temperature. Piecewise-linear conditions (Treska or Ishlinsky-Ivlev), in contrast to the Mises condition, make it possible to obtain solutions of the equilibrium equation in an analytical form. In the problem under consideration, using the conditions of Tresca, it is impossible to obtain a solution. This is due to the fact that the equation of equilibrium ceases to be satisfied when the two Tresca conditions are fulfilled at once. Using the conditions of plastic flow Ishlinsky-Ivlev allows one to solve the problem. At the same time, there are also no solutions on the edge of the Ishlinsky-Ivlev hexagon in the plane-stressed state. Therefore, the authors of the article propose to jump from the edge to the edge of the mine edge, which gives an opportunity to obtain an analytical solution. At the same time, there is also no solution on the edge of the Ishlinsky-Ivlev hexagon in a plane stressed state; therefore, in this paper, the authors of the article propose to jump from the side to the side of the mine edge, which gives an opportunity to receive an analytical solution. The paper compares solutions of the problem of plate thermal deformation. One of the solutions was obtained under the condition that the elastic moduli (Young's modulus, Poisson's ratio) which depend on temperature. The yield point is assumed to be parabolically temperature dependent. The main results of the comparisons are that the region of irreversible deformation is larger in the calculations obtained for solving the problem with constant elastic moduli. There is no repeated plastic flow in the solution of the problem with elastic moduli depending on temperature. The absolute value of the irreversible deformations is higher for the solution of the problem in which the elastic moduli are constant; there are also insignificant differences in the distribution of the residual stresses.

Keywords: temperature stresses, elasticity, plasticity, Ishlinsky-Ivlev condition, plate, annular heating, elastic moduli

Procedia PDF Downloads 134

Authors: Mustafa Kamoona, Mohamed El-Sharkawy

Abstract:

Although the latest Wireless Local Area Network technology Wi-Fi 802.11i standard addresses many of the security weaknesses of the antecedent Wired Equivalent Privacy (WEP) protocol, there are still scenarios where the network security are still vulnerable. The first security model that 802.11i offers is the Personal model which is very cheap and simple to install and maintain, yet it uses a Pre Shared Key (PSK) and thus has a low to medium security level. The second model that 802.11i provide is the Enterprise model which is highly secured but much more expensive and difficult to install/maintain and requires the installation and maintenance of an authentication server that will handle the authentication and key management for the wireless network. A central issue with the personal model is that the PSK needs to be shared with all the devices that are connected to the specific Wi-Fi network. This pre-shared key, unless changed regularly, can be cracked using offline dictionary attacks within a matter of hours. The key is burdensome to change in all the connected devices manually unless there is some kind of algorithm that coordinate this PSK update. The key idea of this paper is to propose a new algorithm that proactively and effectively coordinates the pre-shared key generation, management, and distribution in the cheap WPA/WPA2 personal security model using only a DD-WRT router.

Keywords: Wi-Fi, WPS, TLS, DD-WRT

Procedia PDF Downloads 221

Authors: Boris G. German, Edward Jiménez, Sebastián Espinoza, Andrés G. Chico, Ricardo A. Narváez

Abstract:

The unique flora and fauna of The Galapagos Islands has leveraged a tourism-driven growth in the islands. Nonetheless, such development is energy-intensive and requires thousands of gallons of diesel each year for thermoelectric electricity generation. The needed transport of fossil fuels from the continent has generated oil spillages and affectations to the fragile ecosystem of the islands. The Zero Fossil Fuels initiative for The Galapagos proposed by the Ecuadorian government as an alternative to reduce the use of fossil fuels in the islands, considers the replacement of diesel in thermoelectric generators, by Jatropha curcas vegetable oil. However, the Jatropha oil supply cannot entirely cover yet the demand for electricity generation in Galapagos. Within this context, the present work aims to provide an optimization model that can be used as a selection criterion for approving new Jatropha Curcas collection points in rural areas of Manabi-Ecuador. For this purpose, existing Jatropha collection points in Manabi were grouped under three regions: north (7 collection points), center (4 collection points) and south (9 collection points). Field work was carried out in every region in order to characterize the collection points, to establish local Jatropha supply and to determine transportation costs. Data collection was complemented using GIS software and an objective function was defined in order to determine the profit associated to Jatropha oil production. The market price of both Jatropha oil and residual cake, were considered for the total revenue; whereas Jatropha price, transportation and oil extraction costs were considered for the total cost. The tonnes of Jatropha fruit and seed, transported from collection points to the extraction plant, were considered as variables. The maximum and minimum amount of the collected Jatropha from each region constrained the optimization problem. The supply chain was optimized using linear programming in order to maximize the profits. Finally, a sensitivity analysis was performed in order to find a profit-based criterion for the acceptance of future collection points in Manabi. The maximum profit reached a value of $ 4,616.93 per year, which represented a total Jatropha collection of 62.3 tonnes Jatropha per year. The northern region of Manabi had the biggest collection share (69%), followed by the southern region (17%). The criteria for accepting new Jatropha collection points in the rural areas of Manabi can be defined by the current maximum profit of the zone and by the variation in the profit when collection points are removed one at a time. The definition of new feasible collection points plays a key role in the supply chain associated to Jatropha oil production. Therefore, a mathematical model that assists decision makers in establishing new collection points while assuring profitability, contributes to guarantee a continued Jatropha oil supply for Galapagos and a sustained economic growth in the rural areas of Ecuador.

Keywords: collection points, Jatropha curcas, linear programming, supply chain

Procedia PDF Downloads 418

Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

Abstract:

In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

Procedia PDF Downloads 210

Authors: Neoclis Hadjigeorgiou, Spyridon Angelopoulos, Evangelos V. Hristoforou, Paul P. Sotiriadis

Abstract:

The increasing demand for accurate and reliable magnetic measurements over the past decades has paved the way for the development of different types of magnetic sensing systems as well as of more advanced measurement techniques. Anisotropic Magneto Resistance (AMR) sensors have emerged as a promising solution for applications requiring high resolution, providing an ideal balance between performance and cost. However, certain issues of AMR sensors such as non-linear response and measurement noise are rarely discussed in the relevant literature. In this work, an analog closed loop compensation system is proposed, developed and tested as a means to eliminate the non-linearity of AMR response, reduce the 1/f noise and enhance the sensitivity of magnetic sensor. Additional performance aspects, such as cross-axis and hysteresis effects are also examined. This system was analyzed using an analytical model and a P-Spice model, considering both the sensor itself as well as the accompanying electronic circuitry. In addition, a commercial closed loop architecture Flux-Gate sensor (calibrated and certified), has been used for comparison purposes. Three different experimental setups have been constructed for the purposes of this work, each one utilized for DC magnetic field measurements, AC magnetic field measurements and Noise density measurements respectively. The DC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to calibrate and characterize the system under consideration. A high-accuracy DC power supply has been used for providing the operating current to the Helmholtz coils. The results were recorded by a multichannel voltmeter The AC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to examine the effective bandwidth not only of the proposed system but also for the Flux-Gate sensor. A voltage controlled current source driven by a function generator has been utilized for the Helmholtz coil excitation. The result was observed by the oscilloscope. The third experimental apparatus incorporated an AC magnetic shielding construction composed of several layers of electric steel that had been demagnetized prior to the experimental process. Each sensor was placed alone and the response was captured by the oscilloscope. The preliminary experimental results indicate that closed loop AMR response presented a maximum deviation of 0.36% with respect to the ideal linear response, while the corresponding values for the open loop AMR system and the Fluxgate sensor reached 2% and 0.01% respectively. Moreover, the noise density of the proposed close loop AMR sensor system remained almost as low as the noise density of the AMR sensor itself, yet considerably higher than that of the Flux-Gate sensor. All relevant numerical data are presented in the paper.

Keywords: AMR sensor, chopper, closed loop, electronic noise, magnetic noise, memory effects, flux-gate sensor, linearity improvement, sensitivity improvement

Procedia PDF Downloads 412

Authors: Keerthi S. Shetty, Annappa Basava

Abstract:

In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.

Keywords: systems biology, probabilistic model, inference, biology, model

Procedia PDF Downloads 334

Authors: H. Namazi, H. T. N. Kuan

Abstract:

Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to auditory stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to auditory stimuli but provide us with very good recommendations for clinical purposes.

Keywords: auditory stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

Procedia PDF Downloads 523

Authors: Elena Puica

Abstract:

This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

Procedia PDF Downloads 106

Authors: Ana Rahma Yuniarti, Ki Moo Lim

Abstract:

Slowed myocardial conduction velocity (CV) and shortened action potential duration (APD) due to some reason are associated with an increased risk of re-entrant excitation, predisposing to cardiac arrhythmia. That is because both of CV reduction and APD shortening induces shortening of wavelength. In this study, we investigated quantitatively the cardiac mechanical responses under various CV and APD using multi-scale computational model of the heart. The model consisted of electrical model coupled with the mechanical contraction model together with a lumped model of the circulatory system. The electrical model consisted of 149.344 numbers of nodes and 183.993 numbers of elements of tetrahedral mesh, whereas the mechanical model consisted of 356 numbers of nodes and 172 numbers of elements of hexahedral mesh with hermite basis. We performed the electrical simulation with two scenarios: 1) by varying the CV values with constant APD and 2) by varying the APD values with constant CV. Then, we compared the electrical and mechanical responses for both scenarios. Our simulation showed that faster CV and longer APD induced largest resultants wavelength and generated better cardiac pumping efficacy by increasing the cardiac output and consuming less energy. This is due to the long wave propagation and faster conduction generated more synchronous contraction of whole ventricle.

Keywords: conduction velocity, action potential duration, mechanical contraction model, circulatory model

Procedia PDF Downloads 193

Authors: M. Mohsin Munir, Taimoor Ahmad, Javed Munir, Usman Rashid

Abstract:

Determination of maximum elevation of a flowing fluid due to sudden rejection of load in a hydropower facility is of great interest to hydraulic engineers to ensure safety of the hydraulic structures. Several mathematical models exist that employ one-dimensional modeling for the determination of surge but none of these perfectly simulate real-time circumstances. The paper envisages investigation of surge inception and propagation for a Low Head Hydropower project using Computational Fluid Dynamics (CFD) analysis on FLOW-3D software package. The fluid dynamic model utilizes its analysis for surge by employing Reynolds’ Averaged Navier-Stokes Equations (RANSE). The CFD model is designed for a case study at Taunsa hydropower Project in Pakistan. Various scenarios have run through the model keeping in view upstream boundary conditions. The prototype results were then compared with the results of physical model testing for the same scenarios. The results of the numerical model proved quite accurate coherence with the physical model testing and offers insight into phenomenon which are not apparent in physical model and shall be adopted in future for the similar low head projects limiting delays and cost incurred in the physical model testing.

Keywords: surge, FLOW-3D, numerical model, Taunsa, RANSE

Procedia PDF Downloads 350