Search results for: vector model

Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

Abstract:

In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: Brain balancing, kNN, power spectral density, 3D EEG model.

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Authors: Afshin Ahmadi Nadooshan, Ebrahim Shirani

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In this paper, the two-dimensional stagger grid interface pressure (SGIP) model has been generalized and presented into three-dimensional form. For this purpose, various models of surface tension force for interfacial flows have been investigated and compared with each other. The VOF method has been used for tracking the interface. To show the ability of the SGIP model for three-dimensional flows in comparison with other models, pressure contours, maximum spurious velocities, norm spurious flow velocities and pressure jump error for motionless drop of liquid and bubble of gas are calculated using different models. It has been pointed out that SGIP model in comparison with the CSF, CSS and PCIL models produces the least maximum and norm spurious velocities. Additionally, the new model produces more accurate results in calculating the pressure jumps across the interface for motionless drop of liquid and bubble of gas which is generated in surface tension force.

Keywords: Volume-of-Fluid; SGIP model; CSS model; CSF model; PCIL model; surface tension force; spurious currents.

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Authors: Christian P. Crisostomo, Chrysline Margus N. Piñol

Abstract:

A zero-field ferromagnetic Ising model is utilized to simulate the propagation of infection in a population that assumes a square lattice structure. The rate of infection increases with temperature. The disease spreads faster among individuals with low J values. Such effect, however, diminishes at higher temperatures.

Keywords: Epidemiology, Ising model, lattice models

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Authors: Hadi Farhadian, Homayoon Katibeh

Abstract:

Groundwater inflow to the tunnels is one of the most important problems in tunneling operation. The objective of this study is the investigation of model dimension effects on tunnel inflow assessment in discontinuous rock masses using numerical modeling. In the numerical simulation, the model dimension has an important role in prediction of water inflow rate. When the model dimension is very small, due to low distance to the tunnel border, the model boundary conditions affect the estimated amount of groundwater flow into the tunnel and results show a very high inflow to tunnel. Hence, in this study, the two-dimensional universal distinct element code (UDEC) used and the impact of different model parameters, such as tunnel radius, joint spacing, horizontal and vertical model domain extent has been evaluated. Results show that the model domain extent is a function of the most significant parameters, which are tunnel radius and joint spacing.

Keywords: Water inflow, Tunnel, Discontinues rock, Numerical simulation.

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Authors: Chimaobi V. Okolo, Onyinye S. Ugwuanyi, Kenneth A. Okpala

Abstract:

This study evaluated the effect of exchange rate volatility on the manufacturing sector of Nigeria. The flow and stock market theories of exchange rate determination was adopted considering macroeconomic determinants such as balance of trade, trade openness, and net international investment. Furthermore, the influence of changes in parallel exchange rate, official exchange rate and real effective exchange rate was modeled on the manufacturing sector output. Vector autoregression techniques and vector error correction mechanism were adopted to explore the macroeconomic determinants of exchange rate fluctuation in Nigeria and to examine the influence of exchange rate volatility on the manufacturing sector output in Nigeria. The exchange rate showed an unstable and volatile movement in Nigeria. Official exchange rate significantly impacted on the manufacturing sector of Nigeria and shock to previous manufacturing sector output caused 60.76% of the fluctuation in the manufacturing sector output in Nigeria. Trade balance, trade openness and net international investments did not significantly determine exchange rate in Nigeria. However, own shock accounted for about 95% of the variation of exchange rate fluctuation in the short-run and long-run. Among other macroeconomic variables, net international investment accounted for about 2.85% variation of the real effective exchange rate fluctuation in the short-run and in the long-run. Monetary authorities should maintain stability of the exchange rates through proper management so as to encourage local production and government should formulate and implement policies that will develop other sectors of the economy as this will widen the country’s revenue base, reduce our over reliance on oil sector for our foreign exchange earnings and in turn reduce the shocks on our domestic economy.

Keywords: Exchange rate volatility, exchange rate determinants, manufacturing sector, official exchange rate, parallel exchange rate, real effective exchange rate.

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Authors: Mehdi Ghayoumi

Abstract:

We have applied new accelerated algorithm for linear discriminate analysis (LDA) in face recognition with support vector machine. The new algorithm has the advantage of optimal selection of the step size. The gradient descent method and new algorithm has been implemented in software and evaluated on the Yale face database B. The eigenfaces of these approaches have been used to training a KNN. Recognition rate with new algorithm is compared with gradient.

Keywords: lda, adaptive, svm, face recognition.

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Authors: Peter Podbreznik, Božidar Potocnik

Abstract:

A camera in the building site is exposed to different weather conditions. Differences between images of the same scene captured with the same camera arise also due to temperature variations. The influence of temperature changes on camera parameters were modelled and integrated into existing analytical camera model. Modified camera model enables quantitatively assessing the influence of temperature variations.

Keywords: camera calibration, analytical model, intrinsic parameters, extrinsic parameters, temperature variations.

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Authors: A. Amar

Abstract:

A new model namely, the crystal model, has been modified to calculate radius and density distribution of light nuclei up to 8Be. The crystal model has been modified according to solid state physics which uses the analogy between nucleon distribution and atoms distribution in the crystal. The model has analytical analysis to calculate the radius where the density distribution of light nuclei has been obtained from the analogy of crystal lattice. The distribution of nucleons over crystal has been discussed in general form. The equation used to calculate binding energy was taken from the solid-state model of repulsive and attractive force. The numbers of the protons were taken to control repulsive force where the atomic number was responsible for the attractive force. The parameter has been calculated from the crystal model was found to be proportional to the radius of the nucleus. The density distribution of light nuclei was taken as a summation of two clusters distribution as in 6Li=alpha+deuteron configuration. A test has been done on the data obtained for radius and density distribution using double folding for d+6,7Li with M3Y nucleon-nucleon interaction. Good agreement has been obtained for both radius and density distribution of light nuclei. The model failed to calculate the radius of 9Be, so modifications should be done to overcome discrepancy.

Keywords: nuclear lattice, crystal model, light nuclei, nuclear density distributions

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Authors: Evgeniy Burlutskiy

Abstract:

The paper presents a one-dimensional transient mathematical model of compressible thermal multi-component gas mixture flows in pipes. The set of the mass, momentum and enthalpy conservation equations for gas phase is solved. Thermo-physical properties of multi-component gas mixture are calculated by solving the Equation of State (EOS) model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. Gas mixture viscosity is calculated on the basis of the Lee-Gonzales-Eakin (LGE) correlation. Numerical analysis on rapid decompression in conventional dry gases is performed by using the proposed mathematical model. The model is validated on measured values of the decompression wave speed in dry natural gas mixtures. All predictions show excellent agreement with the experimental data at high and low pressure. The presented model predicts the decompression in dry natural gas mixtures much better than GASDECOM and OLGA codes, which are the most frequently-used codes in oil and gas pipeline transport service.

Keywords: Mathematical model, Rapid Gas Decompression

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Authors: Valentina Koliskina

Abstract:

Change in impedance of an encircling coil is obtained in the present paper for the case where the electric conductivity and magnetic permeability of a metal cylindrical tube depend on the radial coordinate. The system of equations for the vector potential is solved by means of the Fourier cosine transform. The solution is expressed in terms of improper integral containing modified Bessel functions of complex order.

Keywords: Eddy currents, magnetic permeability, Besselfunctions

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Authors: Afshari H., Khosravi Sh.

Abstract:

Nowadays there are more than thirty maturity models in different knowledge areas. Maturity model is an area of interest that contributes organizations to find out where they are in a specific knowledge area and how to improve it. As Information Resource Management (IRM) is the concept that information is a major corporate resource and must be managed using the same basic principles used to manage other assets, assessment of the current IRM status and reveal the improvement points can play a critical role in developing an appropriate information structure in organizations. In this paper we proposed a framework for information resource management maturity model (IRM3) that includes ten best practices for the maturity assessment of the organizations' IRM.

Keywords: Information resource management (IRM), information resource management maturity model (IRM3), maturity model, best practice.

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Authors: Chenxi Yang, Zhouhong Li

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This paper is concerned with an epidemic model with delay. By using the comparison theorem of the differential equation and constructing a suitable Lyapunov functional, Some sufficient conditions which guarantee the permeance and existence of a unique globally attractive positive almost periodic solution of the model are obtain. Finally, an example is employed to illustrate our result.

Keywords: Permanence, Almost periodic solution, Epidemic model, Delay, Feedback control.

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Authors: Tae in Seol, Sun-Tae Chung, Seongwon Cho

Abstract:

Realistic 3D face model is desired in various applications such as face recognition, games, avatars, animations, and etc. Construction of 3D face model is composed of 1) building a face shape model and 2) rendering the face shape model. Thus, building a realistic 3D face shape model is an essential step for realistic 3D face model. Recently, 3D morphable model is successfully introduced to deal with the various human face shapes. 3D dense correspondence problem should be precedently resolved for constructing a realistic 3D dense morphable face shape model. Several approaches to 3D dense correspondence problem in 3D face modeling have been proposed previously, and among them optical flow based algorithms and TPS (Thin Plate Spline) based algorithms are representative. Optical flow based algorithms require texture information of faces, which is sensitive to variation of illumination. In TPS based algorithms proposed so far, TPS process is performed on the 2D projection representation in cylindrical coordinates of the 3D face data, not directly on the 3D face data and thus errors due to distortion in data during 2D TPS process may be inevitable. In this paper, we propose a new 3D dense correspondence algorithm for 3D dense morphable face shape modeling. The proposed algorithm does not need texture information and applies TPS directly on 3D face data. Through construction procedures, it is observed that the proposed algorithm constructs realistic 3D face morphable model reliably and fast.

Keywords: 3D Dense Correspondence, 3D Morphable Face Shape Model, 3D Face Modeling.

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Authors: Huan Xiong, Ming Chen

Abstract:

In order to research Internet quantificationally and better model the performance of network, this paper proposes a novel AS level network performance model (MNPM), it takes autonomous system (AS) as basic modeling unit, measures E2E performance between any two outdegrees of an AS and organizes measurement results into matrix form which called performance matrix (PM). Inter-AS performance calculation is defined according to performance information stored in PM. Simulation has been implemented to verify the correctness of MNPM and a practical application of MNPM (network congestion detection) is given.

Keywords: AS, network performance, model, metric, congestion.

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Authors: Shilpi Lavania, Deepak Nagaria

Abstract:

A mixed method for model order reduction is presented in this paper. The denominator polynomial is derived by matching both Markov parameters and time moments, whereas numerator polynomial derivation and error minimization is done using Genetic Algorithm. The efficiency of the proposed method can be investigated in terms of closeness of the response of reduced order model with respect to that of higher order original model and a comparison of the integral square error as well.

Keywords: Model Order Reduction (MOR), control theory, Markov parameters, time moments, genetic algorithm, Single Input Single Output (SISO).

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

Abstract:

The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: Artificial Neural Networks, ANNs, classifier algorithms, credit risk assessment, logistic regression, machine learning, support vector machines.

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Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov

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For optimal unbiased filter as mean-square and in the case of functioning anomalous noises in the observation memory channel, we have proved insensitivity of filter to inaccurate knowledge of the anomalous noise intensity matrix and its equivalence to truncated filter plotted only by non anomalous components of an observation vector.

Keywords: Mathematical expectation, filtration, anomalous noise, memory.

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Authors: Prasad Senadheera, Younousse Saidi, Frans JM Maathuis

Abstract:

Rice seed expression (cDNA) library in the Lambda Zap 11® phage constructed from the developing grain 10-20 days after flowering was transformed into yeast for functional complementation assays in three salt sensitive yeast mutants S. cerevisiae strain CY162, G19 and Axt3K. Transformed cells of G19 and Axt3K with pYES vector with cDNA inserts showed enhance tolerance than those with empty pYes vector. Sequencing of the cDNA inserts revealed that they encode for the putative proteins with the sequence homologous to rice putative protein PROLM24 (Os06g31070), a prolamin precursor. Expression of this cDNA did not affect yeast growth in absence of salt. Axt3k and G19 strains expressing the PROLM24 were able to grow upto 400 mM and 600 mM of NaCl respectively. Similarly, Axt3k mutant with PROLM24 expression showed comparatively higher growth rate in the medium with excess LiCl (50 mM). The observation that expression of PROLM24 rescued the salt sensitive phenotypes of G19 and Axt3k indicates the existence of a regulatory system that ameliorates the effect of salt stress in the transformed yeast mutants. However, the exact function of the cDNA sequence, which shows partial sequence homology to yeast UTR1 is not clear. Although UTR1 involved in ferrous uptake and iron homeostasis in yeast cells, there is no evidence to prove its role in Na+ homeostasis in yeast cells. Absence of transmembrane regions in Os06g31070 protein indicates that salt tolerance is achieved not through the direct functional complementation of the mutant genes but through an alternative mechanism.

Keywords: Rice seed expression, salt stress, prolamin, salinitytolerance, Oryza sativa

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Authors: Bin Wang, Hengyu Ji, Zhifeng Ye

Abstract:

Fuel Metering Unit (FMU) in fuel system of an aeroengine sometimes has direct influence on the engine performance, which is neglected for the sake of easy access to mathematical model of the engine in most cases. In order to verify the influence of FMU on an engine model, this paper presents a co-simulation of a stepping motor driven FMU (digital FMU) in a turboshaft aeroengine, using AMESim and MATLAB to obtain the steady and dynamic characteristics of the FMU. For this method, mechanical and hydraulic section of the unit is modeled through AMESim, while the stepping motor is mathematically modeled through MATLAB/Simulink. Combining these two sub-models yields an AMESim/MATLAB co-model of the FMU. A simplified component level model for the turboshaft engine is established and connected with the FMU model. Simulation results on the full model show that the engine model considering FMU characteristics describes the engine more precisely especially in its transition state. An FMU dynamics will cut down the rotation speed of the high pressure shaft and the inlet pressure of the combustor during the step response. The work in this paper reveals the impact of FMU on engine operation characteristics and provides a reference to an engine model for ground tests.

Keywords: Fuel metering unit, stepping motor, AMESim/MATLAB, full digital simulation.

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Authors: Amr Abdel Azim Ali, G. A. Elsheikh, Moutaz Hegazy

Abstract:

This paper presents verification of a modeling and simulation for a Spacecraft (SC) attitude and orbit control system. Detailed formulation of coupled SC orbital and attitude equations of motion is performed in order to achieve accepted accuracy to meet the requirements of multitargets tracking and orbit correction complex modes. Correction of the target parameter based on the estimated state vector during shooting time to enhance pointing accuracy is considered. Time-optimal nonlinear feedback control technique was used in order to take full advantage of the maximum torques that the controller can deliver. This simulation provides options for visualizing SC trajectory and attitude in a 3D environment by including an interface with V-Realm Builder and VR Sink in Simulink/MATLAB. Verification data confirms the simulation results, ensuring that the model and the proposed control law can be used successfully for large and fast tracking and is robust enough to keep the pointing accuracy within the desired limits with considerable uncertainty in inertia and control torque.

Keywords: Attitude and orbit control, time-optimal nonlinear feedback control, modeling and simulation, pointing accuracy, maximum torques.

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Authors: Evgeniy Burlutskiy

Abstract:

The paper presents a one-dimensional transient mathematical model of compressible non-isothermal multicomponent fluid mixture flow in a pipe. The set of the mass, momentum and enthalpy conservation equations for gas phase is solved in the model. Thermo-physical properties of multi-component gas mixture are calculated by solving the Equation of State (EOS) model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. Gas mixture viscosity is calculated on the basis of the Lee-Gonzales- Eakin (LGE) correlation. Numerical analysis of rapid gas decompression process in rich and base natural gases is made on the basis of the proposed mathematical model. The model is successfully validated on the experimental data [1]. The proposed mathematical model shows a very good agreement with the experimental data [1] in a wide range of pressure values and predicts the decompression in rich and base gas mixtures much better than analytical and mathematical models, which are available from the open source literature.

Keywords: Mathematical model, Multi-Component gas mixture flow, Rapid Gas Decompression

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Authors: Amirhossein Chambari, Seyed Habib Rahmaty, Vahid Hajipour, Aida Karimi

Abstract:

This paper proposes a bi-objective model for the facility location problem under a congestion system. The idea of the model is motivated by applications of locating servers in bank automated teller machines (ATMS), communication networks, and so on. This model can be specifically considered for situations in which fixed service facilities are congested by stochastic demand within queueing framework. We formulate this model with two perspectives simultaneously: (i) customers and (ii) service provider. The objectives of the model are to minimize (i) the total expected travelling and waiting time and (ii) the average facility idle-time. This model represents a mixed-integer nonlinear programming problem which belongs to the class of NP-hard problems. In addition, to solve the model, two metaheuristic algorithms including nondominated sorting genetic algorithms (NSGA-II) and non-dominated ranking genetic algorithms (NRGA) are proposed. Besides, to evaluate the performance of the two algorithms some numerical examples are produced and analyzed with some metrics to determine which algorithm works better.

Keywords: Queuing, Location, Bi-objective, NSGA-II, NRGA

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Authors: A.H. Akhaveissy

Abstract:

Nonlinear finite element method and Serendipity eight nodes element are used for determining of ground surface settlement due to tunneling. Linear element with elastic behavior is used for modeling of lining. Modified Generalized plasticity model with nonassociated flow rule is applied for analysis of a tunnel in Sao Paulo – Brazil. The tunnel had analyzed by Lades- model with 16 parameters. In this work modified Generalized Plasticity is used with 10 parameters, also Mohr-Coulomb model is used to analysis the tunnel. The results show good agreement with observed results of field data by modified Generalized Plasticity model than other models. The obtained result by Mohr-Coulomb model shows less settlement than other model due to excavation.

Keywords: Non-associated flow rule, Generalized plasticity, tunnel excavation, Excavation method.

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Authors: Xing Li, Chengqing Zong

Abstract:

This paper presents an effective framework for Chinesesyntactic parsing, which includes two parts. The first one is a parsing framework, which is based on an improved bottom-up chart parsingalgorithm, and integrates the idea of the beam search strategy of N bestalgorithm and heuristic function of A* algorithm for pruning, then get multiple parsing trees. The second is a novel evaluation model, which integrates contextual and partial lexical information into traditional PCFG model and defines a new score function. Using this model, the tree with the highest score is found out as the best parsing tree. Finally,the contrasting experiment results are given. Keywords?syntactic parsing, PCFG, pruning, evaluation model.

Keywords: syntactic parsing, PCFG, pruning, evaluation model.

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Authors: J. Ramírez A., A. Rubiano F.

Abstract:

In this paper the direct kinematic model of a multiple applications three degrees of freedom industrial manipulator, was developed using the homogeneous transformation matrices and the Denavit - Hartenberg parameters, likewise the inverse kinematic model was developed using the same method, verifying that in the workload border the inverse kinematic presents considerable errors, therefore a genetic algorithm was implemented to optimize the model improving greatly the efficiency of the model.

Keywords: Direct Kinematic, Genetic Algorithm, InverseKinematic, Optimization, Robot Manipulator

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

Abstract:

Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R²).

Keywords: Time series modelling, stochastic processes, ARIMA model, Karkheh River.

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Authors: N.Vahdatifar, Ss.Mortazavi, R.Kianinezhad

Abstract:

In this paper, a Neural Network based predictive DTC algorithm is proposed .This approach is used as an alternative to classical approaches .An appropriate riate Feed - forward network is chosen and based on its value of derivative electromagnetic torque ; optimal stator voltage vector is determined to be applied to the induction motor (by inverter). Moreover, an appropriate torque and flux observer is proposed.

Keywords: Neural Networks, Predictive DTC

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Authors: C. E. Madubueze, S. C. Madubueze, S. Ajama

Abstract:

Cholera is a disease that is predominately common in developing countries due to poor sanitation and overcrowding population. In this paper, a deterministic model for the dynamics of cholera is developed and control measures such as health educational message, therapeutic treatment, and vaccination are incorporated in the model. The effective reproduction number is computed in terms of the model parameters. The existence and stability of the equilibrium states, disease free and endemic equilibrium states are established and showed to be locally and globally asymptotically stable when R0 < 1 and R0 > 1 respectively. The existence of backward bifurcation of the model is investigated. Furthermore, numerical simulation of the model developed is carried out to show the impact of the control measures and the result indicates that combined control measures will help to reduce the spread of cholera in the population.

Keywords: Backward bifurcation, cholera, equilibrium, dynamics, stability.

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Authors: S. H. Lim, T. Furukawa

Abstract:

This paper presents a generalized form of the mechanistic deconvolution technique (GMD) to modeling image sensors applicable in various pan–tilt planes of view. The mechanistic deconvolution technique (UMD) is modified with the given angles of a pan–tilt plane of view to formulate constraint parameters and characterize distortion effects, and thereby, determine the corrected image data. This, as a result, does not require experimental setup or calibration. Due to the mechanistic nature of the sensor model, the necessity for the sensor image plane to be orthogonal to its z-axis is eliminated, and it reduces the dependency on image data. An experiment was constructed to evaluate the accuracy of a model created by GMD and its insensitivity to changes in sensor properties and in pan and tilt angles. This was compared with a pre-calibrated model and a model created by UMD using two sensors with different specifications. It achieved similar accuracy with one-seventh the number of iterations and attained lower mean error by a factor of 2.4 when compared to the pre-calibrated and UMD model respectively. The model has also shown itself to be robust and, in comparison to pre-calibrated and UMD model, improved the accuracy significantly.

Keywords: Image sensor modeling, mechanistic deconvolution, calibration, lens distortion

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

Abstract:

This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining.

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