Search results for: groundwater recharge model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7526

Search results for: groundwater recharge model

7166 Simulating and Forecasting Qualitative Marcoeconomic Models Using Rule-Based Fuzzy Cognitive Maps

Authors: Spiros Mazarakis, George Matzavinos, Peter P. Groumpos

Abstract:

Economic models are complex dynamic systems with a lot of uncertainties and fuzzy data. Conventional modeling approaches using well known methods and techniques cannot provide realistic and satisfactory answers to today-s challenging economic problems. Qualitative modeling using fuzzy logic and intelligent system theories can be used to model macroeconomic models. Fuzzy Cognitive maps (FCM) is a new method been used to model the dynamic behavior of complex systems. For the first time FCMs and the Mamdani Model of Intelligent control is used to model macroeconomic models. This new model is referred as the Mamdani Rule-Based Fuzzy Cognitive Map (MBFCM) and provides the academic and research community with a new promising integrated advanced computational model. A new economic model is developed for a qualitative approach to Macroeconomic modeling. Fuzzy Controllers for such models are designed. Simulation results for an economic scenario are provided and extensively discussed

Keywords: Macroeconomic Models, Mamdani Rule Based- FCMs(MBFCMs), Qualitative and Dynamics System, Simulation.

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7165 Characterization of Novel Atrazine-Degrading Klebsiella sp. isolated from Thai Agricultural Soil

Authors: Sawangjit Sopid

Abstract:

Atrazine, a herbicide widely used in sugarcane and corn production, is a frequently detected groundwater contaminant. An atrazine-degrading bacterium, strain KB02, was obtained from long-term atrazine-treated sugarcane field soils in Kanchanaburi province of Thailand. Strain KB02 had a rod-to-coccus morphological cycle during growth. Sequence analysis of the PCR product indicated that the 16S rRNA gene in strain KB02 was ranging from 97-98% identical to the same region in Klebsiella sp. Based on biochemical, physiological analysis and 16S rDNA sequence analysis of one representative isolate, strain KB02, the isolates belong to the genus Klebsiella in the family Enterobacteriaceae. Interestingly that the various primers for atzA, B and C failed to amplify genomic DNA of strain KB02. Whereas the expected PCR product of atzA, B and C were obtained from the reference strain, Arthrobacter sp. strain KU001.

Keywords: Atrazine, atz gene, Biodegradation, bioremediation, Klebsiella

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7164 Classification of Soil Aptness to Establish of Panicum virgatum in Mississippi using Sensitivity Analysis and GIS

Authors: Eduardo F. Arias, William Cooke III, Zhaofei Fan, William Kingery

Abstract:

During the last decade Panicum virgatum, known as Switchgrass, has been broadly studied because of its remarkable attributes as a substitute pasture and as a functional biofuel source. The objective of this investigation was to establish soil suitability for Switchgrass in the State of Mississippi. A linear weighted additive model was developed to forecast soil suitability. Multicriteria analysis and Sensitivity analysis were utilized to adjust and optimize the model. The model was fit using seven years of field data associated with soils characteristics collected from Natural Resources Conservation System - United States Department of Agriculture (NRCS-USDA). The best model was selected by correlating calculated biomass yield with each model's soils-based output for Switchgrass suitability. Coefficient of determination (r2) was the decisive factor used to establish the 'best' soil suitability model. Coefficients associated with the 'best' model were implemented within a Geographic Information System (GIS) to create a map of relative soil suitability for Switchgrass in Mississippi. A Geodatabase associated with soil parameters was built and is available for future Geographic Information System use.

Keywords: Aptness, GIS, sensitivity analysis, switchgrass, soil.

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7163 Advertisement Effectiveness for Print Media: A Conceptual Model

Authors: Prateek Maheshwari, Nitin Seth, Anoop Kumar Gupta

Abstract:

The objective of present research paper is to highlight the importance of measuring advertisement effectiveness in print media and to develop a conceptual model for advertisement effectiveness. The developed model is based on dimensions on which advertisement effectiveness depends and on the dimensions which are used to measure the effectiveness. An in-depth and extensive literature review is carried out to understand the concept of advertisement effectiveness and its various determinants in context of print media. Based on the insights gained, a conceptual framework for advertisement effectiveness is presented. The model is an attempt to uncover the relatively less explored area of advertisement effectiveness in Indian advertising scenario. It is believed that present work will encourage scholars and academicians to further explore the area and will offer conceptual assistance and a fresh direction in the domain of advertisement effectiveness.

Keywords: Advertisement Effectiveness, Conceptual Model, Effectiveness Dimensions, Print Media.

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7162 Modeling and Control of a Quadrotor UAV with Aerodynamic Concepts

Authors: Wei Dong, Guo-Ying Gu, Xiangyang Zhu, Han Ding

Abstract:

This paper presents preliminary results on modeling and control of a quadrotor UAV. With aerodynamic concepts, a mathematical model is firstly proposed to describe the dynamics of the quadrotor UAV. Parameters of this model are identified by experiments with Matlab Identify Toolbox. A group of PID controllers are then designed based on the developed model. To verify the developed model and controllers, simulations and experiments for altitude control, position control and trajectory tracking are carried out. The results show that the quadrotor UAV well follows the referenced commands, which clearly demonstrates the effectiveness of the proposed approach.

Keywords: Quadrotor UAV, Modeling, Control, Aerodynamics, System Identification.

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7161 An Improved C-Means Model for MRI Segmentation

Authors: Ying Shen, Weihua Zhu

Abstract:

Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: Magnetic Resonance Image, C-means model, image segmentation, information entropy.

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7160 On the Efficiency and Robustness of Commingle Wiener and Lévy Driven Processes for Vasciek Model

Authors: Rasaki O. Olanrewaju

Abstract:

The driven processes of Wiener and Lévy are known self-standing Gaussian-Markov processes for fitting non-linear dynamical Vasciek model. In this paper, a coincidental Gaussian density stationarity condition and autocorrelation function of the two driven processes were established. This led to the conflation of Wiener and Lévy processes so as to investigate the efficiency of estimates incorporated into the one-dimensional Vasciek model that was estimated via the Maximum Likelihood (ML) technique. The conditional laws of drift, diffusion and stationarity process was ascertained for the individual Wiener and Lévy processes as well as the commingle of the two processes for a fixed effect and Autoregressive like Vasciek model when subjected to financial series; exchange rate of Naira-CFA Franc. In addition, the model performance error of the sub-merged driven process was miniature compared to the self-standing driven process of Wiener and Lévy.

Keywords: Wiener process, Lévy process, Vasciek model, drift, diffusion, Gaussian density stationary.

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7159 Multi-Line Power Flow Control using Interline Power Flow Controller (IPFC) in Power Transmission Systems

Authors: A.V.Naresh Babu, S.Sivanagaraju, Ch.Padmanabharaju, T.Ramana

Abstract:

The interline power flow controller (IPFC) is one of the latest generation flexible AC transmission systems (FACTS) controller used to control power flows of multiple transmission lines. This paper presents a mathematical model of IPFC, termed as power injection model (PIM). This model is incorporated in Newton- Raphson (NR) power flow algorithm to study the power flow control in transmission lines in which IPFC is placed. A program in MATLAB has been written in order to extend conventional NR algorithm based on this model. Numerical results are carried out on a standard 2 machine 5 bus system. The results without and with IPFC are compared in terms of voltages, active and reactive power flows to demonstrate the performance of the IPFC model.

Keywords: flexible AC transmission systems (FACTS), interline power flow controller (IPFC), power injection model (PIM), power flow control.

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7158 An Improved Limited Tolerance Rough Set Model

Authors: Chen Wu, Komal Narejo, Dandan Li

Abstract:

Some extended rough set models in incomplete information system cannot distinguish the two objects that have few known attributes and more unknown attributes; some cannot make a flexible and accurate discrimination. In order to solve this problem, this paper suggests an improved limited tolerance rough set model using two thresholds to control what two objects have a relationship between them in limited tolerance relation and to classify objects. Our practical study case shows the model can get fine and reasonable decision results.

Keywords: Decision rule, incomplete information system, limited tolerance relation, rough set model.

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7157 Bootstrap Confidence Intervals and Parameter Estimation for Zero Inflated Strict Arcsine Model

Authors: Y. N. Phang, E. F. Loh

Abstract:

Zero inflated Strict Arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, maximum likelihood estimation method is used in estimating the parameters for zero inflated strict arcsine model. Bootstrapping is then employed to compute the confidence intervals for the estimated parameters.

Keywords: overdispersed count data, maximum likelihood estimation, simulated annealing, BCa confidence intervals.

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7156 Finite Element Modeling of Stockbridge Damper and Vibration Analysis: Equivalent Cable Stiffness

Authors: Nitish Kumar Vaja, Oumar Barry, Brian DeJong

Abstract:

Aeolian vibrations are the major cause for the failure of conductor cables. Using a Stockbridge damper reduces these vibrations and increases the life span of the conductor cable. Designing an efficient Stockbridge damper that suits the conductor cable requires a robust mathematical model with minimum assumptions. However it is not easy to analytically model the complex geometry of the messenger. Therefore an equivalent stiffness must be determined so that it can be used in the analytical model. This paper examines the bending stiffness of the cable and discusses the effect of this stiffness on the natural frequencies. The obtained equivalent stiffness compensates for the assumption of modeling the messenger as a rod. The results from the free vibration analysis of the analytical model with the equivalent stiffness is validated using the full scale finite element model of the Stockbridge damper.

Keywords: Equivalent stiffness, finite element model, free vibration response, Stockbridge damper.

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7155 Development of a Model for the Redesign of Plant Structures

Authors: L. Richter, J. Lübkemann, P. Nyhuis

Abstract:

In order to remain competitive in what is a turbulent environment; businesses must be able to react rapidly to change. The past response to volatile market conditions was to introduce an element of flexibility to production. Nowadays, what is often required is a redesign of factory structures in order to cope with the state of constant flux. The Institute of Production Systems and Logistics is currently developing a descriptive and causal model for the redesign of plant structures as part of an ongoing research project. This article presents the first research findings attained in devising this model.

Keywords: Causal model, change driven factory redesign, factory planning, plant structure.

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7154 Operating Model of Obstructive Sleep Apnea Patients in North Karelia Central Hospital

Authors: L. Korpinen, T. Kava, I. Salmi

Abstract:

This study aimed to describe the operating model of obstructive sleep apnea. Due to the large number of patients, the role of nurses in the diagnosis and treatment of sleep apnea was important. Pulmonary physicians met only a minority of the patients. The sleep apnea study in 2018 included about 800 patients, of which about 28% were normal and 180 patients were classified as severe (apnea-hypopnea index [AHI] over 30). The operating model has proven to be workable and appropriate. The patients understand well that they may not be referred to a pulmonary doctor. However, specialized medical follow-up on professional drivers continues every year.

Keywords: Sleep, apnea patient, operating model, hospital.

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7153 Development of EREC IF Model to Increase Critical Thinking and Creativity Skills of Undergraduate Nursing Students

Authors: Kamolrat Turner, Boontuan Wattanakul

Abstract:

Critical thinking and creativity are prerequisite skills for working professionals in the 21st century. A survey conducted in 2014 at the Boromarajonani College of Nursing, Chon Buri, Thailand, revealed that these skills within students across all academic years was at a low to moderate level. An action research study was conducted to develop the EREC IF Model, a framework which includes the concepts of experience, reflection, engagement, culture and language, ICT, and flexibility and fun, to guide pedagogic activities for 75 sophomores of the undergraduate nursing science program at the college. The model was applied to all professional nursing courses. Prior to implementation, workshops were held to prepare lecturers and students. Both lecturers and students initially expressed their discomfort and pointed to the difficulties with the model. However, later they felt more comfortable, and by the end of the project they expressed their understanding and appreciation of the model. A survey conducted four and eight months after implementation found that the critical thinking and creativity skills of the sophomores were significantly higher than those recorded in the pretest. It could be concluded that the EREC IF model is efficient for fostering critical thinking and creativity skills in the undergraduate nursing science program. This model should be used for other levels of students.

Keywords: Critical thinking, creativity, undergraduate nursing students, EREC IF model.

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7152 Investigation on Machine Tools Energy Consumptions

Authors: Shiva Abdoli, Daniel T. Semere

Abstract:

Several researches have been conducted to study consumption of energy in cutting process. Most of these researches are focusing to measure the consumption and propose consumption reduction methods. In this work, the relation between the cutting parameters and the consumption is investigated in order to establish a generalized energy consumption model that can be used for process and production planning in real production lines. Using the generalized model, the process planning will be carried out by taking into account the energy as a function of the selected process parameters. Similarly, the generalized model can be used in production planning to select the right operational parameters like batch sizes, routing, buffer size, etc. in a production line. The description and derivation of the model as well as a case study are given in this paper to illustrate the applicability and validity of the model.

Keywords: Process parameters, cutting process, energy efficiency, Material Removal Rate (MRR).

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7151 Validation of Building Maintenance Performance Model for Malaysian Universities

Authors: AbdulLateef A. Olanrewaju, Mohd F. Khamidi, Arazi Idrus

Abstract:

This paper is part of an ongoing research on the development of systemic maintenance management model Malaysian university buildings. In order to achieve this aim, there is a need to develop a performance model against which services are measure. Measuring performance is a significant part of maintenance management service delivery. Maintenance organization needs to know where they are in order to provide user-driven services and to enhance productivity. The aim of this paper is to formulate a template or model for university maintenance organization in Malaysia. The model is based on literature review and survey questionnaire and has been validated. Through grounded theory, this paper developed a 8 points matrix for the university maintenance organizations for measuring and improving their service delivery. The potential of the model is guide and assists towards providing value added service delivery through initiating maintenance according to user value system rather than on the condition of the building.

Keywords: Performance matrix, university buildings, users, maintenance organization

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7150 Modeling the Human Cardiovascular System with Aspecial Focus on the Heart Using Dymola

Authors: Stefanie Heinke, Carina Pereira, Jan Spillner, Steffen Leonhardt

Abstract:

Severe heart failure is a common problem that has a significant effect on health expenditures in industrialized countries; moreover it reduces patient-s quality of life. However, current research usually focuses either on detailed modeling of the heart or on detailed modeling of the cardiovascular system. Thus, this paper aims to present a sophisticated model of the heart enhanced with an extensive model of the cardiovascular system. Special interest is on the pressure and flow values close to the heart since these values are critical to accurately diagnose causes of heart failure. The model is implemented in Dymola an object-oriented, physical modeling language. Results achieved with the novel model show overall feasibility of the approach. Moreover, results are illustrated and compared to other models. The novel model shows significant improvements.

Keywords: Cardiovascular system, heart, modeling.

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7149 A new Cellular Automata Model of Cardiac Action Potential Propagation based on Summation of Excited Neighbors

Authors: F. Pourhasanzade, S. H. Sabzpoushan

Abstract:

The heart tissue is an excitable media. A Cellular Automata is a type of model that can be used to model cardiac action potential propagation. One of the advantages of this approach against the methods based on differential equations is its high speed in large scale simulations. Recent cellular automata models are not able to avoid flat edges in the result patterns or have large neighborhoods. In this paper, we present a new model to eliminate flat edges by minimum number of neighbors.

Keywords: Cellular Automata, Action Potential Simulation, Isotropic Pattern.

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7148 Two States Mapping Based Neural Network Model for Decreasing of Prediction Residual Error

Authors: Insung Jung, lockjo Koo, Gi-Nam Wang

Abstract:

The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.

Keywords: Neural network, U-healthcare, prediction, timeseries, computer aided prediction.

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7147 Dual-Network Memory Model for Temporal Sequences

Authors: Motonobu Hattori, Rina Suzuki

Abstract:

In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudopatterns. Because temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional  dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.  

Keywords: Catastrophic forgetting, dual-network, temporal sequences.

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7146 A Nonlinear ODE System for the Unsteady Hydrodynamic Force – A New Approach

Authors: Osama A. Marzouk

Abstract:

We propose a reduced-ordermodel for the instantaneous hydrodynamic force on a cylinder. The model consists of a system of two ordinary differential equations (ODEs), which can be integrated in time to yield very accurate histories of the resultant force and its direction. In contrast to several existing models, the proposed model considers the actual (total) hydrodynamic force rather than its perpendicular or parallel projection (the lift and drag), and captures the complete force rather than the oscillatory part only. We study and provide descriptions of the relationship between the model parameters, evaluated utilizing results from numerical simulations, and the Reynolds number so that the model can be used at any arbitrary value within the considered range of 100 to 500 to provide accurate representation of the force without the need to perform timeconsuming simulations and solving the partial differential equations (PDEs) governing the flow field.

Keywords: reduced-order model, wake oscillator, nonlinear, ODEsystem

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7145 A Boundary Fitted Nested Grid Model for Modelling Tsunami Propagation of 2004 Indonesian Tsunami along Southern Thailand

Authors: Md. Fazlul Karim, Esa Al-Islam

Abstract:

This paper describes the development of a boundary fitted nested grid (BFNG) model to compute tsunami propagation of 2004 Indonesian tsunami in Southern Thailand coastal waters. We develop a numerical model employing the shallow water nested model and an orthogonal boundary fitted grid to investigate the tsunami impact on the Southern Thailand due to the Indonesian tsunami of 2004. Comparisons of water surface elevation obtained from numerical simulations and field measurements are made.

Keywords: Boundary-fitted nested grid model, finite difference method, Indonesian tsunami of 2004, Southern Thailand.

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7144 A Comparative Analysis of the Performance of COSMO and WRF Models in Quantitative Rainfall Prediction

Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

Abstract:

The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: Comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events.

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7143 Application of Build-up and Wash-off Models for an East-Australian Catchment

Authors: Iqbal Hossain, Monzur Alam Imteaz, Mohammed Iqbal Hossain

Abstract:

Estimation of stormwater pollutants is a pre-requisite for the protection and improvement of the aquatic environment and for appropriate management options. The usual practice for the stormwater quality prediction is performed through water quality modeling. However, the accuracy of the prediction by the models depends on the proper estimation of model parameters. This paper presents the estimation of model parameters for a catchment water quality model developed for the continuous simulation of stormwater pollutants from a catchment to the catchment outlet. The model is capable of simulating the accumulation and transportation of the stormwater pollutants; suspended solids (SS), total nitrogen (TN) and total phosphorus (TP) from a particular catchment. Rainfall and water quality data were collected for the Hotham Creek Catchment (HTCC), Gold Coast, Australia. Runoff calculations from the developed model were compared with the calculated discharges from the widely used hydrological models, WBNM and DRAINS. Based on the measured water quality data, model water quality parameters were calibrated for the above-mentioned catchment. The calibrated parameters are expected to be helpful for the best management practices (BMPs) of the region. Sensitivity analyses of the estimated parameters were performed to assess the impacts of the model parameters on overall model estimations of runoff water quality.

Keywords: Calibration, Model Parameters, Suspended Solids, TotalNitrogen, Total Phosphorus.

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7142 Application of Company Financial Crisis Early Warning Model- Use of “Financial Reference Database“

Authors: Chiung-ying Lee, Chia-hua Chang

Abstract:

In July 1, 2007, Taiwan Stock Exchange (TWSE) on market observation post system (MOPS) adds a new "Financial reference database" for investors to do investment reference. This database as a warning to public offering companies listed on the public financial information and it original within eight targets. In this paper, this database provided by the indicators for the application of company financial crisis early warning model verify that the database provided by the indicator forecast for the financial crisis, whether or not companies have a high accuracy rate as opposed to domestic and foreign scholars have positive results. There is use of Logistic Regression Model application of the financial early warning model, in which no joined back-conditions is the first model, joined it in is the second model, has been taken occurred in the financial crisis of companies to research samples and then business took place before the financial crisis point with T-1 and T-2 sample data to do positive analysis. The results show that this database provided the debt ratio and net per share for the best forecast variables.

Keywords: Financial reference database, Financial early warning model, Logistic Regression.

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7141 A Scheme of Model Verification of the Concurrent Discrete Wavelet Transform (DWT) for Image Compression

Authors: Kamrul Hasan Talukder, Koichi Harada

Abstract:

The scientific community has invested a great deal of effort in the fields of discrete wavelet transform in the last few decades. Discrete wavelet transform (DWT) associated with the vector quantization has been proved to be a very useful tool for the compression of image. However, the DWT is very computationally intensive process requiring innovative and computationally efficient method to obtain the image compression. The concurrent transformation of the image can be an important solution to this problem. This paper proposes a model of concurrent DWT for image compression. Additionally, the formal verification of the model has also been performed. Here the Symbolic Model Verifier (SMV) has been used as the formal verification tool. The system has been modeled in SMV and some properties have been verified formally.

Keywords: Computation Tree Logic, Discrete WaveletTransform, Formal Verification, Image Compression, Symbolic Model Verifier.

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7140 Spatial Time Series Models for Rice and Cassava Yields Based On Bayesian Linear Mixed Models

Authors: Panudet Saengseedam, Nanthachai Kantanantha

Abstract:

This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, Linear mixed model, Multivariate conditional autoregressive model, Spatial time series.

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7139 A New Time Dependent, High Temperature Analytical Model for the Single-electron Box in Digital Applications

Authors: M.J. Sharifi

Abstract:

Several models have been introduced so far for single electron box, SEB, which all of them were restricted to DC response and or low temperature limit. In this paper we introduce a new time dependent, high temperature analytical model for SEB for the first time. DC behavior of the introduced model will be verified against SIMON software and its time behavior will be verified against a newly published paper regarding step response of SEB.

Keywords: Single electron box, SPICE, SIMON, Timedependent, Circuit model.

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7138 Identification of Micromechanical Fracture Model for Predicting Fracture Performance of Steel Wires for Civil Engineering Applications

Authors: Kazeem K. Adewole, Julia M. Race, Steve J. Bull

Abstract:

The fracture performance of steel wires for civil engineering applications remains a major concern in civil engineering construction and maintenance of wire reinforced structures. The need to employ approaches that simulate micromechanical material processes which characterizes fracture in civil structures has been emphasized recently in the literature. However, choosing from the numerous micromechanics-based fracture models, and identifying their applicability and reliability remains an issue that still needs to be addressed in a greater depth. Laboratory tensile testing and finite element tensile testing simulations with the shear, ductile and Gurson-Tvergaard-Needleman’s micromechanics-based models conducted in this work reveal that the shear fracture model is an appropriate fracture model to predict the fracture performance of steel wires used for civil engineering applications. The need to consider the capability of the micromechanics-based fracture model to predict the “cup and cone” fracture exhibited by the wire in choosing the appropriate fracture model is demonstrated.

Keywords: Fracture performance, FE simulation, Shear fracture model, Ductile fracture model, Gurson-Tvergaard-Needleman fracture model, Wires.

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7137 A Combinatorial Model for ECG Interpretation

Authors: Costas S. Iliopoulos, Spiros Michalakopoulos

Abstract:

A new, combinatorial model for analyzing and inter- preting an electrocardiogram (ECG) is presented. An application of the model is QRS peak detection. This is demonstrated with an online algorithm, which is shown to be space as well as time efficient. Experimental results on the MIT-BIH Arrhythmia database show that this novel approach is promising. Further uses for this approach are discussed, such as taking advantage of its small memory requirements and interpreting large amounts of pre-recorded ECG data.

Keywords: Combinatorics, ECG analysis, MIT-BIH Arrhythmia Database, QRS Detection, String Algorithms

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