Search results for: generalised linear modelling.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2289

Search results for: generalised linear modelling.

639 Seismic Performance Evaluation of Bridge Structures Using 3D Finite Element Methods in South Korea

Authors: Woo Young Jung, Bu Seog Ju

Abstract:

This study described the seismic performance evaluation of bridge structures, located near Daegu metropolitan city in Korea. The structural design code or regulatory guidelines is focusing on the protection of brittle failure or collapse in bridges’ lifetime during an earthquake. This paper illustrated the procedure in terms of the safety evaluation of bridges using simple linear elastic 3D Finite Element (FE) model in ABAQUS platform. The design response spectra based on KBC 2009 were then developed, in order to understand the seismic behavior of bridge structures. Besides, the multiple directional earthquakes were applied and it revealed that the most dominated earthquake direction was transverse direction of the bridge. Also, the bridge structure under the compressive stress was more fragile than the tensile stress and the vertical direction of seismic ground motions was not significantly affected to the structural system.

Keywords: Bridge, Finite Element, 3D model, Earthquake, Spectrum.

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638 Short-Term Electric Load Forecasting Using Multiple Gaussian Process Models

Authors: Tomohiro Hachino, Hitoshi Takata, Seiji Fukushima, Yasutaka Igarashi

Abstract:

This paper presents a Gaussian process model-based short-term electric load forecasting. The Gaussian process model is a nonparametric model and the output of the model has Gaussian distribution with mean and variance. The multiple Gaussian process models as every hour ahead predictors are used to forecast future electric load demands up to 24 hours ahead in accordance with the direct forecasting approach. The separable least-squares approach that combines the linear least-squares method and genetic algorithm is applied to train these Gaussian process models. Simulation results are shown to demonstrate the effectiveness of the proposed electric load forecasting.

Keywords: Direct method, electric load forecasting, Gaussian process model, genetic algorithm, separable least-squares method.

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637 Development of In Situ Permeability Test Using Constant Discharge Method for Sandy Soils

Authors: A. Rifa’i, Y. Takeshita, M. Komatsu

Abstract:

The post-rain puddles problem that occurs in the first yard of Prambanan Temple are often disturbing visitor activity. A poodle layer and a drainage system had ever built to avoid such a problem, but puddles still did not stop appearing after rain. Permeability parameter needs to be determined by using a simpler procedure to find exact method of solution. The instrument modelling was proposed according to the development of field permeability testing instrument. This experiment used a proposed Constant Discharge method. Constant Discharge method used a tube poured with constant water flow from unsaturated until saturated soil condition. Volumetric water content (θ) were monitored by soil moisture measurement device. The results were correlations between k and θ which were drawn by numerical approach from Van Genutchen model. Parameters θr optimum value obtained from the test was at very dry soil. Coefficient of permeability with a density of 19.8 kN/m3 for unsaturated conditions was in range of 3 x 10-6 cm/sec (Sr=68%) until 9.98 x 10-4 cm/sec (Sr=82%). The equipment and testing procedure developed in this research was quite effective, simple and easy to be implemented on determining field soil permeability coefficient value of sandy soil. Using constant discharge method in proposed permeability test, value of permeability coefficient under unsaturated condition can be obtained without establish soil water characteristic curve.

Keywords: Constant discharge method, in situ permeability test, sandy soil, unsaturated conditions.

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636 Hydrological Characterization of a Watershed for Streamflow Prediction

Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

Abstract:

In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: Hydrological characteristic, land and climate, runoff discharge, streamflow.

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635 Microfluidic Paper-Based Electrochemical Biosensor

Authors: Ahmad Manbohi, Seyyed Hamid Ahmadi

Abstract:

A low-cost paper-based microfluidic device (PAD) for the multiplex electrochemical determination of glucose, uric acid, and dopamine in biological fluids was developed. Using wax printing, PAD containing a central zone, six channels, and six detection zones was fabricated, and the electrodes were printed on detection zones using pre-made electrodes template. For each analyte, two detection zones were used. The carbon working electrode was coated with chitosan-BSA (and enzymes for glucose and uric acid). To detect glucose and uric acid, enzymatic reactions were employed. These reactions involve enzyme-catalyzed redox reactions of the analytes and produce free electrons for electrochemical measurement. Calibration curves were linear (R² > 0.980) in the range of 0-80 mM for glucose, 0.09–0.9 mM for dopamine, and 0–50 mM for uric acid, respectively. Blood samples were successfully analyzed by the proposed method.

Keywords: Multiplex, microfluidic paper-based electrochemical biosensors, biomarkers, biological fluids.

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634 Application of Transportation Linear Programming Algorithms to Cost Reduction in Nigeria Soft Drinks Industry

Authors: A. O. Salami

Abstract:

The transportation problems are primarily concerned with the optimal way in which products produced at different plants (supply origins) are transported to a number of warehouses or customers (demand destinations). The objective in a transportation problem is to fully satisfy the destination requirements within the operating production capacity constraints at the minimum possible cost. The objective of this study is to determine ways of minimizing transportation cost in order to maximum profit. Data were sourced from the records of the Distribution Department of 7-Up Bottling Company Plc., Ilorin, Kwara State, Nigeria. The data were computed and analyzed using the three methods of solving transportation problem. The result shows that the three methods produced the same total transportation costs amounting to N1, 358, 019, implying that any of the method can be adopted by the company in transporting its final products to the wholesale dealers in order to minimize total production cost. 

Keywords: Allocation problem, Cost Minimization, Distribution system, Resources utilization.

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633 Spatial Correlation of Channel State Information in Real LoRa Measurement

Authors: Ahmed Abdelghany, Bernard Uguen, Christophe Moy, Dominique Lemur

Abstract:

The Internet of Things (IoT) is developed to ensure monitoring and connectivity within different applications. Thus, it is critical to study the channel propagation characteristics in Low Power Wide Area Network (LPWAN), especially LoRaWAN. In this paper, an in-depth investigation of the reciprocity between the uplink and downlink Channel State Information (CSI) is done by performing an outdoor measurement campaign in the area of Campus Beaulieu in Rennes. At each different location, the CSI reciprocity is quantified using the Pearson Correlation Coefficient (PCC) which shows a very high linear correlation between the uplink and downlink CSI. This reciprocity feature could be utilized for the physical layer security between the node and the gateway. On the other hand, most of the CSI shapes from different locations are highly uncorrelated with each other. Hence, it can be anticipated that this could achieve significant localization gain by utilizing the frequency hopping in the LoRa systems to get access to a wider band.

Keywords: IoT, LPWAN, LoRa, RSSI, effective signal power, onsite measurement, smart city, channel reciprocity.

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632 Fourier Galerkin Approach to Wave Equation with Absorbing Boundary Conditions

Authors: Alexandra Leukauf, Alexander Schirrer, Emir Talic

Abstract:

Numerical computation of wave propagation in a large domain usually requires significant computational effort. Hence, the considered domain must be truncated to a smaller domain of interest. In addition, special boundary conditions, which absorb the outward travelling waves, need to be implemented in order to describe the system domains correctly. In this work, the linear one dimensional wave equation is approximated by utilizing the Fourier Galerkin approach. Furthermore, the artificial boundaries are realized with absorbing boundary conditions. Within this work, a systematic work flow for setting up the wave problem, including the absorbing boundary conditions, is proposed. As a result, a convenient modal system description with an effective absorbing boundary formulation is established. Moreover, the truncated model shows high accuracy compared to the global domain.

Keywords: Absorbing boundary conditions, boundary control, Fourier Galerkin approach, modal approach, wave equation.

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631 Ground Motion Modelling in Bangladesh Using Stochastic Method

Authors: Mizan Ahmed, Srikanth Venkatesan

Abstract:

Geological and tectonic framework indicates that Bangladesh is one of the most seismically active regions in the world. The Bengal Basin is at the junction of three major interacting plates: the Indian, Eurasian, and Burma Plates. Besides there are many active faults within the region, e.g. the large Dauki fault in the north. The country has experienced a number of destructive earthquakes due to the movement of these active faults. Current seismic provisions of Bangladesh are mostly based on earthquake data prior to the 1990. Given the record of earthquakes post 1990, there is a need to revisit the design provisions of the code. This paper compares the base shear demand of three major cities in Bangladesh: Dhaka (the capital city), Sylhet, and Chittagong for earthquake scenarios of magnitudes 7.0MW, 7.5MW, 8.0MW, and 8.5MW using a stochastic model. In particular, the stochastic model allows the flexibility to input region specific parameters such as shear wave velocity profile (that were developed from Global Crustal Model CRUST2.0) and include the effects of attenuation as individual components. Effects of soil amplification were analysed using the Extended Component Attenuation Model (ECAM). Results show that the estimated base shear demand is higher in comparison with code provisions leading to the suggestion of additional seismic design consideration in the study regions.

Keywords: Attenuation, earthquake, ground motion, stochastic, seismic hazard.

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630 Improved Lung Nodule Visualization on Chest Radiographs using Digital Filtering and Contrast Enhancement

Authors: Benjamin Y. M. Kwan, Hon Keung Kwan

Abstract:

Early detection of lung cancer through chest radiography is a widely used method due to its relatively affordable cost. In this paper, an approach to improve lung nodule visualization on chest radiographs is presented. The approach makes use of linear phase high-frequency emphasis filter for digital filtering and histogram equalization for contrast enhancement to achieve improvements. Results obtained indicate that a filtered image can reveal sharper edges and provide more details. Also, contrast enhancement offers a way to further enhance the global (or local) visualization by equalizing the histogram of the pixel values within the whole image (or a region of interest). The work aims to improve lung nodule visualization of chest radiographs to aid detection of lung cancer which is currently the leading cause of cancer deaths worldwide.

Keywords: Chest radiographs, Contrast enhancement, Digital filtering, Lung nodule detection

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629 Dynamic Fuzzy-Neural Network Controller for Induction Motor Drive

Authors: M. Zerikat, M. Bendjebbar, N. Benouzza

Abstract:

In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.

Keywords: Induction motor, fuzzy-logic control, neural network control, indirect field oriented control.

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628 Forecasting Stock Indexes Using Bayesian Additive Regression Tree

Authors: Darren Zou

Abstract:

Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: Bayesian, Forecast, Stock, BART.

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627 Optimal Current Control of Externally Excited Synchronous Machines in Automotive Traction Drive Applications

Authors: Oliver Haala, Bernhard Wagner, Maximilian Hofmann, Martin Marz

Abstract:

The excellent suitability of the externally excited synchronous machine (EESM) in automotive traction drive applications is justified by its high efficiency over the whole operation range and the high availability of materials. Usually, maximum efficiency is obtained by modelling each single loss and minimizing the sum of all losses. As a result, the quality of the optimization highly depends on the precision of the model. Moreover, it requires accurate knowledge of the saturation dependent machine inductances. Therefore, the present contribution proposes a method to minimize the overall losses of a salient pole EESM and its inverter in steady state operation based on measurement data only. Since this method does not require any manufacturer data, it is well suited for an automated measurement data evaluation and inverter parametrization. The field oriented control (FOC) of an EESM provides three current components resp. three degrees of freedom (DOF). An analytic minimization of the copper losses in the stator and the rotor (assuming constant inductances) is performed and serves as a first approximation of how to choose the optimal current reference values. After a numeric offline minimization of the overall losses based on measurement data the results are compared to a control strategy that satisfies cos (ϕ) = 1.

Keywords: Current control, efficiency, externally excited synchronous machine, optimization.

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626 The Non-Stationary BINARMA(1,1) Process with Poisson Innovations: An Application on Accident Data

Authors: Y. Sunecher, N. Mamode Khan, V. Jowaheer

Abstract:

This paper considers the modelling of a non-stationary bivariate integer-valued autoregressive moving average of order one (BINARMA(1,1)) with correlated Poisson innovations. The BINARMA(1,1) model is specified using the binomial thinning operator and by assuming that the cross-correlation between the two series is induced by the innovation terms only. Based on these assumptions, the non-stationary marginal and joint moments of the BINARMA(1,1) are derived iteratively by using some initial stationary moments. As regards to the estimation of parameters of the proposed model, the conditional maximum likelihood (CML) estimation method is derived based on thinning and convolution properties. The forecasting equations of the BINARMA(1,1) model are also derived. A simulation study is also proposed where BINARMA(1,1) count data are generated using a multivariate Poisson R code for the innovation terms. The performance of the BINARMA(1,1) model is then assessed through a simulation experiment and the mean estimates of the model parameters obtained are all efficient, based on their standard errors. The proposed model is then used to analyse a real-life accident data on the motorway in Mauritius, based on some covariates: policemen, daily patrol, speed cameras, traffic lights and roundabouts. The BINARMA(1,1) model is applied on the accident data and the CML estimates clearly indicate a significant impact of the covariates on the number of accidents on the motorway in Mauritius. The forecasting equations also provide reliable one-step ahead forecasts.

Keywords: Non-stationary, BINARMA(1, 1) model, Poisson Innovations, CML

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625 Conventional Synthesis and Characterization of Zirconium Molybdate, Nd2Zr3(MoO4)9

Authors: G. Çelik Gül, F. Kurtuluş

Abstract:

Rare earths containing complex metal oxides have drawn much attention due to physical, chemical and optical properties which make them feasible in so many areas such as non-linear optical materials and ion exchanger. We have researched a systematic study to obtain rare earth containing zirconium molybdate compound, characterization, investigation of crystal system and calculation of unit cell parameters.  After a successful synthesis of Nd2Zr3(MoO4)9 which is a member of rare earth metal containing complex oxides family, X-ray diffraction (XRD), High Score Plus/Rietveld refinement analysis, and Fourier Transform Infrared Spectroscopy (FTIR) were completed to determine the crystal structure. Morphological properties and elemental composition were determined by scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) analysis. Thermal properties were observed via Thermogravimetric-differential thermal analysis (TG/DTA).

Keywords: Nd2Zr3(MoO4)9, solid state synthesis, powder x-ray diffraction, zirconium molybdates.

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624 Particle Swarm Optimization Based Genetic Algorithm for Two-Stage Transportation Supply Chain

Authors: Siva Prasad Darla, C. D. Naiju, K. Annamalai, S. S. Rajiv Sushanth

Abstract:

Supply chain consists of all stages involved, directly or indirectly, includes all functions involved in fulfilling a customer demand. In two stage transportation supply chain problem, transportation costs are of a significant proportion of final product costs. It is often crucial for successful decisions making approaches in two stage supply chain to explicit account for non-linear transportation costs. In this paper, deterministic demand and finite supply of products was considered. The optimized distribution level and the routing structure from the manufacturing plants to the distribution centres and to the end customers is determined using developed mathematical model and solved by proposed particle swarm optimization based genetic algorithm. Numerical analysis of the case study is carried out to validate the model.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Production, Remanufacturing

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623 Design of a Low Power Compensated 90nm RF Multiplier with Improved Isolation Characteristics for a Transmitted Reference Receiver Front End

Authors: Apratim Roy, A. B. M. H. Rashid

Abstract:

In this paper, a double balanced radio frequency multiplier is presented which is customized for transmitted reference ultra wideband (UWB) receivers. The multiplier uses 90nm model parameters and exploits compensating transistors to provide controllable gain for a Gilbert core. After performing periodic and quasiperiodic non linear analyses the RF mixer (multiplier) achieves a voltage conversion gain of 16 dB and a DSB noise figure of 8.253 dB with very low power consumption. A high degree of LO to RF isolation (in the range of -94dB), RF to IF isolation (in the range of -95dB) and LO to IF isolation (in the range of -143dB) is expected for this design with an input-referred IP3 point of -1.93 dBm and an input referred 1 dB compression point of -10.67dBm. The amount of noise at the output is 7.7 nV/√Hz when the LO input is driven by a 10dBm signal. The mixer manifests better results when compared with other reported multiplier circuits and its Zero-IF performance ensures its applicability as TR-UWB multipliers.

Keywords: UWB, Transmitted Reference, Controllable Gain, RFMixer, Multiplier.

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622 Impact of Viscous and Heat Relaxation Loss on the Critical Temperature Gradients of Thermoacoustic Stacks

Authors: Zhibin Yu, Artur J. Jaworski, Abdulrahman S. Abduljalil

Abstract:

A stack with a small critical temperature gradient is desirable for a standing wave thermoacoustic engine to obtain a low onset temperature difference (the minimum temperature difference to start engine-s self-oscillation). The viscous and heat relaxation loss in the stack determines the critical temperature gradient. In this work, a dimensionless critical temperature gradient factor is obtained based on the linear thermoacoustic theory. It is indicated that the impedance determines the proportion between the viscous loss, heat relaxation losses and the power production from the heat energy. It reveals the effects of the channel dimensions, geometrical configuration and the local acoustic impedance on the critical temperature gradient in stacks. The numerical analysis shows that there exists a possible optimum combination of these parameters which leads to the lowest critical temperature gradient. Furthermore, several different geometries have been tested and compared numerically.

Keywords: Critical temperature gradient, heat relaxation, stack, viscous effect.

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621 A Mathematical Investigation of the Turkevich Organizer Theory in the Citrate Method for the Synthesis of Gold Nanoparticles

Authors: Emmanuel Agunloye, Asterios Gavriilidis, Luca Mazzei

Abstract:

Gold nanoparticles are commonly synthesized by reducing chloroauric acid with sodium citrate. This method, referred to as the citrate method, can produce spherical gold nanoparticles (NPs) in the size range 10-150 nm. Gold NPs of this size are useful in many applications. However, the NPs are usually polydisperse and irreproducible. A better understanding of the synthesis mechanisms is thus required. This work thoroughly investigated the only model that describes the synthesis. This model combines mass and population balance equations, describing the NPs synthesis through a sequence of chemical reactions. Chloroauric acid reacts with sodium citrate to form aurous chloride and dicarboxy acetone. The latter organizes aurous chloride in a nucleation step and concurrently degrades into acetone. The unconsumed precursor then grows the formed nuclei. However, depending on the pH, both the precursor and the reducing agent react differently thus affecting the synthesis. In this work, we investigated the model for different conditions of pH, temperature and initial reactant concentrations. To solve the model, we used Parsival, a commercial numerical code, whilst to test it, we considered various conditions studied experimentally by different researchers, for which results are available in the literature. The model poorly predicted the experimental data. We believe that this is because the model does not account for the acid-base properties of both chloroauric acid and sodium citrate.

Keywords: Gold nanoparticles, Citrate method, Turkevich organizer theory, population balance modelling.

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620 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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619 Two Dimensionnal Model for Extraction Packed Column Simulation using Finite Element Method

Authors: N. Outili, A-H. Meniai

Abstract:

Modeling transfer phenomena in several chemical engineering operations leads to the resolution of partial differential equations systems. According to the complexity of the operations mechanisms, the equations present a nonlinear form and analytical solution became difficult, we have then to use numerical methods which are based on approximations in order to transform a differential system to an algebraic one.Finite element method is one of numerical methods which can be used to obtain an accurate solution in many complex cases of chemical engineering.The packed columns find a large application like contactor for liquid-liquid systems such solvent extraction. In the literature, the modeling of this type of equipment received less attention in comparison with the plate columns.A mathematical bidimensionnal model with radial and axial dispersion, simulating packed tower extraction behavior was developed and a partial differential equation was solved using the finite element method by adopting the Galerkine model. We developed a Mathcad program, which can be used for a similar equations and concentration profiles are obtained along the column. The influence of radial dispersion was prooved and it can-t be neglected, the results were compared with experimental concentration at the top of the column in the extraction system: acetone/toluene/water.

Keywords: finite element method, Galerkine method, liquidliquid extraction modelling, packed column simulation, two dimensional model

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618 Improving the LDMOS Temperature Compensation Bias Circuit to Optimize Back-Off

Authors: Antonis Constantinides, Christos Yiallouras, Christakis Damianou

Abstract:

The application of today's semiconductor transistors in high power UHF DVB-T linear amplifiers has evolved significantly by utilizing LDMOS technology. This fact provides engineers with the option to design a single transistor signal amplifier which enables output power and linearity that was unobtainable previously using bipolar junction transistors or later type first generation MOSFETS. The quiescent current stability in terms of thermal variations of the LDMOS guarantees a robust operation in any topology of DVB-T signal amplifiers. Otherwise, progressively uncontrolled heat dissipation enhancement on the LDMOS case can degrade the amplifier’s crucial parameters in regards to the gain, linearity and RF stability, resulting in dysfunctional operation or a total destruction of the unit. This paper presents one more sophisticated approach from the traditional biasing circuits used so far in LDMOS DVB-T amplifiers. It utilizes a microprocessor control technology, providing stability in topologies where IDQ must be perfectly accurate.

Keywords: Amplifier, DVB-T, LDMOS, MOSFETS.

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617 Time-Frequency Modeling and Analysis of Faulty Rotor

Authors: B. X. Tchomeni, A. A. Alugongo, T. B. Tengen

Abstract:

In this paper, de Laval rotor system has been characterized by a hinge model and its transient response numerically treated for a dynamic solution. The effect of the ensuing non-linear disturbances namely rub and breathing crack is numerically simulated. Subsequently, three analysis methods: Orbit Analysis, Fast Fourier Transform (FFT), and Wavelet Transform (WT) are employed to extract features of the vibration signal of the faulty system. An analysis of the system response orbits clearly indicates the perturbations due to the rotor-to-stator contact. The sensitivities of WT to the variation in system speed have been investigated by Continuous Wavelet Transform (CWT). The analysis reveals that features of crack, rubs and unbalance in vibration response can be useful for condition monitoring. WT reveals its ability to detect nonlinear signal, and obtained results provide a useful tool method for detecting machinery faults.

Keywords: Continuous wavelet, crack, discrete wavelet, high acceleration, low acceleration, nonlinear, rotor-stator, rub.

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616 Detection of Defects in CFRP by Ultrasonic IR Thermographic Method

Authors: W. Swiderski

Abstract:

In the paper introduced the diagnostic technique making possible the research of internal structures in composite materials reinforced fibres using in different applications. The main reason of damages in structures of these materials is the changing distribution of load in constructions in the lifetime. Appearing defect is largely complicated because of the appearance of disturbing of continuity of reinforced fibres, binder cracks and loss of fibres adhesiveness from binders. Defect in composite materials is usually more complicated than in metals. At present, infrared thermography is the most effective method in non-destructive testing composite. One of IR thermography methods used in non-destructive evaluation is vibrothermography. The vibrothermography is not a new non-destructive method, but the new solution in this test is use ultrasonic waves to thermal stimulation of materials. In this paper, both modelling and experimental results which illustrate the advantages and limitations of ultrasonic IR thermography in inspecting composite materials will be presented. The ThermoSon computer program for computing 3D dynamic temperature distribuions in anisotropic layered solids with subsurface defects subject to ulrasonic stimulation was used to optimise heating parameters in the detection of subsurface defects in composite materials. The program allows for the analysis of transient heat conduction and ultrasonic wave propagation phenomena in solids. The experiments at MIAT were fulfilled by means of FLIR SC 7600 IR camera. Ultrasonic stimulation was performed with the frequency from 15 kHz to 30 kHz with maximum power up to 2 kW.

Keywords: Composite material, ultrasonic, infrared thermography, non-destructive testing.

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615 Mamdani Model based Adaptive Neural Fuzzy Inference System and its Application

Authors: Yuanyuan Chai, Limin Jia, Zundong Zhang

Abstract:

Hybrid algorithm is the hot issue in Computational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classification method and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy Inference System (M-ANFIS) and weight updating formula in consideration with qualitative representation of inference consequent parts in fuzzy neural networks. M-ANFIS model adopts Mamdani fuzzy inference system which has advantages in consequent part. Experiment results of applying M-ANFIS to evaluate traffic Level of service show that M-ANFIS, as a new hybrid algorithm in computational intelligence, has great advantages in non-linear modeling, membership functions in consequent parts, scale of training data and amount of adjusted parameters.

Keywords: Fuzzy neural networks, Mamdani fuzzy inference, M-ANFIS

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614 Mathematical Modeling of an Avalanche Release and Estimation of Flow Parameters by Numerical Method

Authors: Mahmoud Zarrini

Abstract:

Avalanche release of snow has been modeled in the present studies. Snow is assumed to be represented by semi-solid and the governing equations have been studied from the concept of continuum approach. The dynamical equations have been solved for two different zones [starting zone and track zone] by using appropriate initial and boundary conditions. Effect of density (ρ), Eddy viscosity (η), Slope angle (θ), Slab depth (R) on the flow parameters have been observed in the present studies. Numerical methods have been employed for computing the non linear differential equations. One of the most interesting and fundamental innovation in the present studies is getting initial condition for the computation of velocity by numerical approach. This information of the velocity has obtained through the concept of fracture mechanics applicable to snow. The results on the flow parameters have found to be in qualitative agreement with the published results.

Keywords: Snow avalanche, fracture mechanics, avalanche velocity, avalanche zones.

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613 Receding Horizon Filtering for Mobile Robot Systems with Cross-Correlated Sensor Noises

Authors: Il Young Song, Du Yong Kim, Vladimir Shin

Abstract:

This paper reports on a receding horizon filtering for mobile robot systems with cross-correlated sensor noises and uncertainties. Also, the effect of uncertain parameters in the state of the tracking error model performance is considered. A distributed fusion receding horizon filter is proposed. The distributed fusion filtering algorithm represents the optimal linear combination of the local filters under the minimum mean square error criterion. The derivation of the error cross-covariances between the local receding horizon filters is the key of this paper. Simulation results of the tracking mobile robot-s motion demonstrate high accuracy and computational efficiency of the distributed fusion receding horizon filter.

Keywords: Distributed fusion, fusion formula, Kalman filter, multisensor, receding horizon, wheeled mobile robot

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612 A Note on the Minimum Cardinality of Critical Sets of Inertias for Irreducible Zero-nonzero Patterns of Order 4

Authors: Ber-Lin Yu, Ting-Zhu Huang

Abstract:

If there exists a nonempty, proper subset S of the set of all (n+1)(n+2)/2 inertias such that S Ôèå i(A) is sufficient for any n×n zero-nonzero pattern A to be inertially arbitrary, then S is called a critical set of inertias for zero-nonzero patterns of order n. If no proper subset of S is a critical set, then S is called a minimal critical set of inertias. In [Kim, Olesky and Driessche, Critical sets of inertias for matrix patterns, Linear and Multilinear Algebra, 57 (3) (2009) 293-306], identifying all minimal critical sets of inertias for n×n zero-nonzero patterns with n ≥ 3 and the minimum cardinality of such a set are posed as two open questions by Kim, Olesky and Driessche. In this note, the minimum cardinality of all critical sets of inertias for 4 × 4 irreducible zero-nonzero patterns is identified.

Keywords: Zero-nonzero pattern, inertia, critical set of inertias, inertially arbitrary.

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611 Discrete Polynomial Moments and Savitzky-Golay Smoothing

Authors: Paul O'Leary, Matthew Harker

Abstract:

This paper presents unified theory for local (Savitzky- Golay) and global polynomial smoothing. The algebraic framework can represent any polynomial approximation and is seamless from low degree local, to high degree global approximations. The representation of the smoothing operator as a projection onto orthonormal basis functions enables the computation of: the covariance matrix for noise propagation through the filter; the noise gain and; the frequency response of the polynomial filters. A virtually perfect Gram polynomial basis is synthesized, whereby polynomials of degree d = 1000 can be synthesized without significant errors. The perfect basis ensures that the filters are strictly polynomial preserving. Given n points and a support length ls = 2m + 1 then the smoothing operator is strictly linear phase for the points xi, i = m+1. . . n-m. The method is demonstrated on geometric surfaces data lying on an invariant 2D lattice.

Keywords: Gram polynomials, Savitzky-Golay Smoothing, Discrete Polynomial Moments

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610 Investigation of Dissolution in Diammonium Hydrogen Phosphate Solutions of Gypsum

Authors: Turan Çalban, Nursel Keskin, Sabri Çolak, Soner Kuşlu

Abstract:

Gypsum (CaSO4.2H2O) is a mineral that is found in large quantities in the Turkey and in the World. In this study, the dissolution of this mineral in the diammonium hydrogen phosphate solutions has been studied. The dissolution and dissolution kinetics of gypsum in diammonium hydrogen phosphate solutions will be useful for evaluating of solid wastes containing gypsum. Parameters such as diammonium hydrogen phosphate concentration, temperature and stirring speed affecting on the dissolution rate of the gypsum in diammonium hydrogen phosphate solutions were investigated. In experimental studies have researched effectiveness of the selected parameters. The dissolution of gypsum were examined in two parts at low and high temperatures. The experimental results were successfully correlated by linear regression using Statistica program. Dissolution curves were evaluated shrinking core models for solidfluid systems. The activation energy was found to be 34.58 kJ/mol and 44.45 kJ/mol for the low and the high temperatures. The dissolution of gypsum was controlled by chemical reaction both low temperatures and high temperatures.

Keywords: Diammonium hydrogen phosphate, Dissolution, Gypsum, Kinetics.

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