Search results for: Roy's adaptation model

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

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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 280

Authors: Idrissa Kayijuka

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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

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Authors: Saba Rahman, Arvind K. Jain, S. D. Bharti, T. K. Datta

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The present study compares the semi-empirical wake-oscillator models that are used to predict vortex-induced vibration of structures. These models include those proposed by Facchinetti, Farshidian, and Dolatabadi, and Skop and Griffin. These models combine a wake oscillator model resembling the Van der Pol oscillator model and a single degree of freedom oscillation model. In order to use these models for estimating the top displacement of chimneys, the first mode vibration of the chimneys is only considered. The modal equation of the chimney constitutes the single degree of freedom model (SDOF). The equations of the wake oscillator model and the SDOF are simultaneously solved using an iterative procedure. The empirical parameters used in the wake-oscillator models are estimated using a newly developed approach, and response is compared with experimental data, which appeared comparable. For carrying out the iterative solution, the ode solver of MATLAB is used. To carry out the comparative study, a tall concrete chimney of height 210m has been chosen with the base diameter as 28m, top diameter as 20m, and thickness as 0.3m. The responses of the chimney are also determined using the linear model proposed by E. Simiu and the deterministic model given in Eurocode. It is observed from the comparative study that the responses predicted by the Facchinetti model and the model proposed by Skop and Griffin are nearly the same, while the model proposed by Fashidian and Dolatabadi predicts a higher response. The linear model without considering the aero-elastic phenomenon provides a less response as compared to the non-linear models. Further, for large damping, the prediction of the response by the Euro code is relatively well compared to those of non-linear models.

Keywords: chimney, deterministic model, van der pol, vortex-induced vibration

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

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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

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Authors: Tengqin Han

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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

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Authors: Mustafa Kamoona, Mohamed El-Sharkawy

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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

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

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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

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Authors: Keerthi S. Shetty, Annappa Basava

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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

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Authors: Elena Puica

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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

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Authors: Ana Rahma Yuniarti, Ki Moo Lim

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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

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Authors: Adriana Sosa, Susana Rincon, Chérif Ben, Diana Cabañas, Juan E. Ruiz, Alejandro Zepeda

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The complex chemical composition (mixtures of ammonium and recalcitrant compounds) of the effluents from the chemical, pharmaceutical and petrochemical industries represents a challenge in their biological treatment. This treatment involves nitrification process that can suffer an inhibition due to the presence of aromatic compounds giving as a result the decrease of the process efficiency. The inhibitory effects on nitrification in the presence of aromatic compounds have already been studied; however a few studies have considered the presence of phenolic compounds in the form of mixtures, which is the form that they are present in real context. For this reason, we realized a kinetic study on the nitrifying process in the presence of different concentrations of a mixture of phenol, o-cresol, m-cresol and p-cresol (0 - 320 mg C/L) in a sequencing batch reactor (SBR). Firstly, the nitrifying process was evaluated in absence of the phenolic mixture (control 1) in a SBR with 2 L working volume and 176 mg/L of nitrogen of microbial protein. Total oxidation of initial ammonium (efficiency; ENH4+ of 100 %) to nitrate (nitrifying yield; YNO3- of 0.95) were obtained with specific rates of ammonium consumption (qN-NH4+) and nitrate production (qN-NO3-) (of 1.11 ± 0.04 h-1 and 0.67 h-1 ± 0.11 respectively. During the phase of acclimation with 40 mg C/L of the phenolic mixture, an inhibitory effect on the nitrifying process was observed, provoking a decrease in ENH4+ and YNO3- (11 and 54 % respectively) as well as in the specific rates (89 y 46 % respectively), being the ammonia oxidizing bacteria (BAO) the most affected. However, in the next cycles without the phenolic mixture (control 2), the nitrifying consortium was able to recover its nitrifying capacity (ENH4+ = 100% and YNO3-=0.98). Afterwards the SBR was fed with 10 mg C/L of the phenolic mixture, obtaining and ENH4+ of 100%, YNO3- and qN-NH4+ 0.62 ± 0.006 and 0.13 ± 0.004 respectively, while the qN-NO3- was 0.49 ± 0.007. Moreover, with the increase of the phenolic concentrations (10-160 mg C/L) and the number of cycles the nitrifying consortium was able to oxidize the ammonia with ENH4+ of 100 % and YNO3- close to 1. However a decrease in the values of the nitrification specific rates and increase in the oxidation in phenolic compounds (70 to 94%) were observed. Finally, in the presence of 320 mg C/L, the nitrifying consortium was able to simultaneously oxidize the ammonia (ENH4+= 100%) and the phenolic mixture (p-cresol>phenol>m-cresol>o-cresol) being the o-cresol the most recalcitrant compound. In all the experiments the use of a SBR allowed a respiratory adaptation of the consortium to oxidize the phenolic mixture achieving greater adaptation of the nitrite-oxidizing bacteria (NOB) than in the ammonia-oxidizing bacteria (AOB).

Keywords: cresol, inhibition, nitrification, phenol, sequencing batch reactor

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

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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

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Authors: Yungtai Lo

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The current study follows an educational intervention on bottle-weaning to simultaneously evaluate the effect of the bottle-weaning intervention on reducing bottle use, daily milk intake from bottles, and daily energy intake in toddlers aged 11 to 13 months. A shared parameter model and a random effects model are used to jointly model bottle use, daily milk intake from bottles, and daily energy intake. We show in the two joint models that the bottle-weaning intervention promotes bottleweaning, and reduces daily milk intake from bottles in toddlers not off bottles and daily energy intake. We also show that the odds of drinking from a bottle were positively associated with the amount of milk intake from bottles and increased daily milk intake from bottles was associated with increased daily energy intake. The effect of bottle use on daily energy intake is through its effect on increasing daily milk intake from bottles that in turn increases daily energy intake.

Keywords: two-part model, semi-continuous variable, joint model, gamma regression, shared parameter model, random effects model

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Authors: T. M. Ismail, M. A. El-Salam

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A mathematical model study was carried out to investigate gasification of biomass fuels using high-temperature air and steam as a gasifying agent using high-temperature air up to 1000°C. In this study, a 2D computational fluid dynamics model was developed to study the gasification process in an updraft gasifier, considering drying, pyrolysis, combustion, and gasification reactions. The gas and solid phases were resolved using a Euler−Euler multiphase approach, with exchange terms for the momentum, mass, and energy. The standard k−ε turbulence model was used in the gas phase, and the particle phase was modeled using the kinetic theory of granular flow. The results show that the present model giving a promising way in its capability and sensitivity for the parameter effects that influence the gasification process.

Keywords: computational fluid dynamics, gasification, biomass fuel, fixed bed gasifier

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Authors: Dheyaa Wajid Abbood, Hanan Hussien Abood

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Stepped cascade has been utilized as a hydraulic structure for years. It has proven to be the least costly aeration system in replenishing dissolved oxygen. Numerical modeling of stepped cascade with end sill is very complicated and challenging because of the high roughness and velocity re circulation regions. Volume of fluid multiphase flow model (VOF) is used .The realizable k-ξ model is chosen to simulate turbulence. The computational results are compared with lab-scale stepped cascade data. The lab –scale model was constructed in the hydraulic laboratory, Al-Mustansiriya University, Iraq. The stepped cascade was 0.23 m wide and consisted of 3 steps each 0.2m high and 0.6 m long with variable end sill. The discharge was varied from 1 to 4 l/s. ANSYS has been employed to simulate the experimental data and their related results. This study shows that ANSYS is able to predict results almost the same as experimental findings in some regions of the structure.

Keywords: stepped cascade weir, aeration, multiphase flow model, ansys

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Authors: R. Monteiro, A. Abarca

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Large scale seismic risk assessment has become increasingly popular to evaluate the physical vulnerability of a given region to seismic events, by putting together hazard, exposure and vulnerability components. This study, developed within the scope of the EU-funded project ITERATE (Improved Tools for Disaster Risk Mitigation in Algeria), explains the steps and expected results for the development of an integrated seismic risk model for assessment of the vulnerability of residential buildings in Northern Algeria. For this purpose, the model foresees the consideration of an updated seismic hazard model, as well as ad-hoc exposure and physical vulnerability models for local residential buildings. The first results of this endeavor, such as the hazard model and a specific taxonomy to be used for the exposure and fragility components of the model are presented, using as starting point the province of Blida, in Algeria. Specific remarks and conclusions regarding the characteristics of the Northern Algerian in-built are then made based on these results.

Keywords: Northern Algeria, risk, seismic hazard, vulnerability

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Authors: M. Kharazmi, M. Zakeri, M. Packirisamy, J. Faraji

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Micro/Nanorobotics or manipulation of nanoparticles by Atomic Force Microscopic (AFM) is one of the most important solutions for controlling the movement of atoms, particles and micro/nano metrics components and assembling of them to design micro/nano-meter tools. Accurate modelling of manipulation requires identification of forces and mechanical knowledge in the Nanoscale which are different from macro world. Due to the importance of the adhesion forces and the interaction of surfaces at the nanoscale several friction models were presented. In this research, friction and normal forces that are applied on the AFM by using of the dynamic bending-torsion model of AFM are obtained based on Hurtado-Kim friction model (HK), Johnson-Kendall-Robert contact model (JKR) and Greenwood-Williamson roughness model (GW). Finally, the effect of standard deviation of asperities height on the normal load, friction force and friction coefficient are studied.

Keywords: atomic force microscopy, contact model, friction coefficient, Greenwood-Williamson model

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Authors: Pouya Molana, Zeinab Alimohammadi

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Determining wind wave characteristics is essential for implementing projects related to Coastal and Marine engineering such as designing coastal and marine structures, estimating sediment transport rates and coastal erosion rates in order to predict significant wave height (H_s), this study applies the third generation spectral wave model, Mike 21 SW, along with CEM model. For SW model calibration and verification, two data sets of meteorology and wave spectroscopy are used. The model was exposed to time-varying wind power and the results showed that difference ratio mean, standard deviation of difference ratio and correlation coefficient in SW model for H_s parameter are 1.102, 0.279 and 0.983, respectively. Whereas, the difference ratio mean, standard deviation and correlation coefficient in The Choice Experiment Method (CEM) for the same parameter are 0.869, 1.317 and 0.8359, respectively. Comparing these expected results it is revealed that the Choice Experiment Method CEM has more errors in comparison to MIKE 21 SW third generation spectral wave model and higher correlation coefficient does not necessarily mean higher accuracy.

Keywords: MIKE 21 SW, CEM method, significant wave height, difference ratio

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Authors: Tobias Huwer, Thomas Bobek, Gunter Spöcker

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Driving forces for enhancements in production are trends like digitalization and individualized production. Currently, such developments are restricted to assembly parts. Thus, complex freeform surfaces are not addressed in this context. The need for efficient use of resources and near-net-shape production will require individualized production of complex shaped workpieces. Due to variations between nominal model and actual geometry, this can lead to changes in operations in Computer-aided process planning (CAPP) to make CAPP manageable for an adaptive serial production. In this context, 3D CAD data can be a key to realizing that objective. Along with developments in the geometrical adaptation, a preceding inspection method based on CAD data is required to support the process planner by finding objective criteria to make decisions about the adaptive manufacturability of workpieces. Nowadays, this kind of decisions is depending on the experience-based knowledge of humans (e.g. process planners) and results in subjective decisions – leading to a variability of workpiece quality and potential failure in production. In this paper, we present an automatic part inspection method, based on design and measurement data, which evaluates actual geometries of single workpiece preforms. The aim is to automatically determine the suitability of the current shape for further machining, and to provide a basis for an objective decision about subsequent adaptive manufacturability. The proposed method is realized by a workflow-based approach, keeping in mind the requirements of industrial applications. Workflows are a well-known design method of standardized processes. Especially in applications like aerospace industry standardization and certification of processes are an important aspect. Function blocks, providing a standardized, event-driven abstraction to algorithms and data exchange, will be used for modeling and execution of inspection workflows. Each analysis step of the inspection, such as positioning of measurement data or checking of geometrical criteria, will be carried out by function blocks. One advantage of this approach is its flexibility to design workflows and to adapt algorithms specific to the application domain. In general, within the specified tolerance range it will be checked if a geometrical adaption is possible. The development of particular function blocks is predicated on workpiece specific information e.g. design data. Furthermore, for different product lifecycle phases, appropriate logics and decision criteria have to be considered. For example, tolerances for geometric deviations are different in type and size for new-part production compared to repair processes. In addition to function blocks, appropriate referencing systems are important. They need to support exact determination of position and orientation of the actual geometries to provide a basis for precise analysis. The presented approach provides an inspection methodology for adaptive and part-individual process chains. The analysis of each workpiece results in an inspection protocol and an objective decision about further manufacturability. A representative application domain is the product lifecycle of turbine blades containing a new-part production and a maintenance process. In both cases, a geometrical adaptation is required to calculate individual production data. In contrast to existing approaches, the proposed initial inspection method provides information to decide between different potential adaptive machining processes.

Keywords: adaptive, CAx, function blocks, turbomachinery

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Authors: Sibel Celik, Hüseyin Ergin

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The paper aims to find the best volatility forecasting model for stock markets in Turkey. For this purpose, we compare performance of different volatility models-both traditional GARCH model and high frequency based volatility models- and conclude that both in pre-crisis and crisis period, the performance of high frequency based volatility models are better than traditional GARCH model. The findings of paper are important for policy makers, financial institutions and investors.

Keywords: volatility, GARCH model, realized volatility, high frequency data

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Authors: Ashley Wei-Ting Wang, Wen-Yau Hsu

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Objectives: The current study applies and expands the Tripartite Model to elaborate the link between non-suicidal self-injury (NSSI) and suicidal behavior. We propose a structural model of NSSI and suicidal risk, in which negative affect (NA) predicts both anxiety and depression, positive affect (PA) predicts depression only, anxiety is linked to NSSI, and depression is linked to suicidal risk. Method: Four hundreds and eighty seven undergraduates participated. Data were collected by administering self-report questionnaires. We performed hierarchical regression and structural equation modeling to test the proposed structural model. Results: The results largely support the proposed structural model, with one exception: anxiety was strongly associated with NSSI and to a lesser extent with suicidal risk. Conclusions: We conclude that the co-occurrence of NSSI and suicidal risk is due to NA and anxiety, and suicidal risk can be differentiated by depression. Further theoretical and practical implications are discussed.

Keywords: non-suicidal self-injury, suicidal risk, anxiety, depression, the tripartite model, hierarchical relationship

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Authors: Shih-Kuei Lin

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The characterization of the arbitrage-free dynamics of interest rates is developed in this study under the presence of Markov jump risks, when the term structure of the interest rates is modeled through simple forward rates. We consider Markov jump risks by allowing randomness in jump sizes, independence between jump sizes and jump times. The Markov jump diffusion model is used to capture empirical phenomena and to accurately describe interest jump risks in a financial market. We derive the arbitrage-free model of simple forward rates under the spot measure. Moreover, the analytical pricing formulas for a cap and a floor are derived under the forward measure when the jump size follows a lognormal distribution. In our empirical analysis, we find that the LIBOR market model with Markov jump risk better accounts for changes from/to different states and different rates.

Keywords: arbitrage-free, cap and floor, Markov jump diffusion model, simple forward rate model, volatility smile, EM algorithm

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Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

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Authors: J. Fernandez, N. Aguilar, R. Fernandez de Canete, J. C. Ramos-Diaz

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In this paper, a simulation model of the glucose-insulin system for a patient undergoing diabetes Type 1 is developed by using a causal modeling approach under system dynamics. The OpenModelica simulation environment has been employed to build the so called causal model, while the glucose-insulin model parameters were adjusted to fit recorded mean data of a diabetic patient database. Model results under different conditions of a three-meal glucose and exogenous insulin ingestion patterns have been obtained. This simulation model can be useful to evaluate glucose-insulin performance in several circumstances, including insulin infusion algorithms in open-loop and decision support systems in closed-loop.

Keywords: causal modeling, diabetes, glucose-insulin system, diabetes, causal modeling, OpenModelica software

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Authors: Bernarette Soust Verdaguer

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Sustainability applied to the built environment has been understood in practice as a strategy to improve efficiency. Its evolution into ecology closer visions are becoming more intense. So the paradigm of regeneration is presented as a complementary alternative to sustainability, emphasizing the association with nature, betting adaptation, recovery and resilience. New design tools and evaluation of built spaces, incorporating this strategy are necessary. In this sense, how it could contribute to the concept of regeneration in built environment design and environmental impacts assessment tools? This paper explores and analyzes some of these keys.

Keywords: sustainability, regeneration, environmental impacts assessment, built environment

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Authors: Tareq Oshan

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Facility location and size decisions are important to any company because they affect profitability and success. However, warehouses are exposed to various risks of failure that affect their activity. This paper presents a mixed-integer non-linear mathematical model that can be used to determine optimal warehouse locations and sizes, which warehouses to fortify, and which branches should be assigned to specific warehouses when there is a risk of warehouse failure. Every branch is assigned to a fortified primary warehouse or a nonfortified primary warehouse and a fortified backup warehouse. The standard method and an introduced method, based on the average probabilities, for linearizing this mathematical model were used. A Canadian case study was used to demonstrate the developed mathematical model, followed by some sensitivity analysis.

Keywords: supply chain network design, fortified warehouse, mixed-integer mathematical model, warehouse failure risk

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Authors: K. M. Anusha, R. Krishnaveni

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Crossing a decade of the 21st century, the paradigm of human resources can be seen evolving with the strategic gene induced into it. There seems to be a radical shift descending as the corporate sector calls on its HR team to become strategic rather than administrative. This transferal eventually requires the metrics employed by these HR teams not to be just operationally reactive but to be aligned to an evidence-based strategic thinking. Realizing the growing need for a prescriptive metric model for effective HR analytics, this study has designed a conceptual framework for a basic metric model that can assist IT-HRM professionals to transition to a practice of evidence-based decision-making to enhance organizational performance.

Keywords: metric model, evidence based HR, HR analytics, strategic HR practices, IT sector

Procedia PDF Downloads 403

Authors: Nikolaos Reppas, Yilin Gui

Abstract:

A dual-porosity finite element-code will be presented for the stability analysis of the wellbore during CO₂ injection. An elastoplastic damage response will be considered to the model. The Finite Element Method (FEM) will be validated using experimental results from literature or from experiments that are planned to be undertaken at Newcastle University. The main target of the research paper is to present a constitutive model that can help industries to safely store CO₂ in geological rock formations and forecast any changes on the surrounding rock of the wellbore. The fully coupled elastoplastic damage Thermo-Hydraulic-Mechanical (THM) model will determine the pressure and temperature of the injected CO₂ as well as the size of the radius of the wellbore that can make the Carbon Capture and Storage (CCS) procedure more efficient.

Keywords: carbon capture and storage, Wellbore stability, elastoplastic damage response for rock, constitutive THM model, fully coupled thermo-hydraulic-mechanical model

Procedia PDF Downloads 172

Authors: N. Guo, C. Xu, Z. C. Yang

Abstract:

In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

Procedia PDF Downloads 161

Authors: Zhan Fengmei Yao, Hui Li, Jiahua Zhang

Abstract:

The Northeast China (NEC) was the most important agriculture areas and known as the Golden-Maize-Belt. Based on observed crop data and crop model, we design four simulating experiments and separate relative impacts and contribution under climate change, planting date shift, and varieties change as well change of varieties and planting date. Without planting date and varieties change, maize yields had no significant change trend at Hailun station located in the north of NEC, and presented significant decrease by 0.2-0.4 t/10a at two stations, which located in the middle and the south of NEC. With planting date change, yields showed a significant increase by 0.09 - 0.47 t/10a. With varieties change, maize yields had significant increase by 1.8~ 1.9 t/10a at Hailun and Huadian stations, but a non-significant and low increase by 0.2t /10a at Benxi located in the south of NEC. With change of varieties and planting date, yields presented a significant increasing by 0.53-2.0 t/10a. Their contribution to yields was -25% ~ -55% for climate change, 15% ~ 35% for planting date change, and 20% ~110% for varieties change as well 30% ~135% for varieties with planting date shift. It found that change in varieties and planting date were highest yields and were responsible for significant increases in maize yields, varieties was secondly, and planting date was thirdly. It found that adaptation in varieties and planting date greatly improved maize yields, and increased yields annual variability. The increase of contribution with planting date and varieties change in 2000s was lower than in 1990s. Yields with the varieties change and yields with planting date and varieties change all showed a decreasing trend at Huadian and Benxi since 2002 or so. It indicated that maize yields increasing trend stagnated in the middle and south of NEC, and continued in the north of NEC.

Keywords: climate change, maize yields, varieties, planting date, impacts

Procedia PDF Downloads 361