Search results for: Maximum Likelihood estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2648

Search results for: Maximum Likelihood estimation

2048 On Adaptive Optimization of Filter Performance Based on Markov Representation for Output Prediction Error

Authors: Hong Son Hoang, Remy Baraille

Abstract:

This paper addresses the problem of how one can improve the performance of a non-optimal filter. First the theoretical question on dynamical representation for a given time correlated random process is studied. It will be demonstrated that for a wide class of random processes, having a canonical form, there exists a dynamical system equivalent in the sense that its output has the same covariance function. It is shown that the dynamical approach is more effective for simulating and estimating a Markov and non- Markovian random processes, computationally is less demanding, especially with increasing of the dimension of simulated processes. Numerical examples and estimation problems in low dimensional systems are given to illustrate the advantages of the approach. A very useful application of the proposed approach is shown for the problem of state estimation in very high dimensional systems. Here a modified filter for data assimilation in an oceanic numerical model is presented which is proved to be very efficient due to introducing a simple Markovian structure for the output prediction error process and adaptive tuning some parameters of the Markov equation.

Keywords: Statistical simulation, canonical form, dynamical system, Markov and non-Markovian processes, data assimilation.

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2047 Estimation of Carbon Released From Dry Dipterocarp Forest Fire in Thailand

Authors: Ubonwan Chaiyo, Yannick Pizzo, Savitri Garivait

Abstract:

This study focused on the estimation of carbon released to the atmosphere from dry dipterocarp forest (DDF) fires in Thailand. Laboratory experiments were conducted using a cone calorimeter to simulate the DDF fires. The leaf litter collected from DDF in western Thailand was used as biomass fuel. Three different masses of leaf litter were employed, 7g, 10g and 13g, to estimate the carbon released from this type of vegetation fire to the atmosphere. The chemical analysis of the leaf litter showed that the carbon content in the experimental biomass fuel was 46.0±0.1%. From the experiments, it was found that more than 95% of the carbon input was converted to carbon released to the atmosphere, while less than 5% were left in the form of residues, and returned to soil. From the study, the carbon released amounted 440.213±2.243 g/kgdry biomass, and the carbon retained in the residues was 19.786±2.243 g/kgdry biomass. The quantity of biomass fuel consumed to produce 1 g of carbon released was 2.27±0.01gkgdry biomass. Using these experimental data of carbon produced by the DDF fires, it was estimated that this type of fires in 2009 contributed to 4.659 tonnes of carbon released to the atmosphere, and 0.229 tonnes of carbon in the residues to be returned to soil in Thailand.

Keywords: Carbon mass balance, carbon released, tropical dry dipterocarp forest, biomass bunring.

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2046 Frequency Response Analysis of Reinforced- Soil Retaining Walls with Polymeric Strips

Authors: Ali Komakpanah, Maryam Yazdi

Abstract:

Few studies have been conducted on polymeric strip and the behavior of soil retaining walls. This paper will present the effect of frequency on the dynamic behavior of reinforced soil retaining walls with polymeric strips. The frequency content describes how the amplitude of a ground motion is distributed among different frequencies. Since the frequency content of an earthquake motion will strongly influence the effects of that motion, the characterization of the motion cannot be completed without the consideration of its frequency content. The maximum axial force of reinforcements and horizontal displacement of the reinforced walls are focused in this research. To clarify the dynamic behavior of reinforced soil retaining walls with polymeric strips, a numerical modeling using Finite Difference Method is benefited. As the results indicate, the frequency of input base acceleration has an important effect on the behavior of these structures. Because of resonant in the system, where the frequency of the input dynamic load is equal to the natural frequency of the system, the maximum horizontal displacement and the maximum axial forces in polymeric strips is occurred. Moreover, they were to increase the structure flexibility because of the main advantages of polymeric strips; i.e. being simple method of construction, having a homogeneous behavior with soils, and possessing long durability, which are of great importance in dynamic analysis.

Keywords: dynamic analysis, frequency, polymeric strip, reinforced soil.

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2045 MaxMin Share Based Medium Access for Attaining Fairness and Channel Utilization in Mobile Adhoc Networks

Authors: P. Priakanth, P. Thangaraj

Abstract:

Due to the complex network architecture, the mobile adhoc network-s multihop feature gives additional problems to the users. When the traffic load at each node gets increased, the additional contention due its traffic pattern might cause the nodes which are close to destination to starve the nodes more away from the destination and also the capacity of network is unable to satisfy the total user-s demand which results in an unfairness problem. In this paper, we propose to create an algorithm to compute the optimal MAC-layer bandwidth assigned to each flow in the network. The bottleneck links contention area determines the fair time share which is necessary to calculate the maximum allowed transmission rate used by each flow. To completely utilize the network resources, we compute two optimal rates namely, the maximum fair share and minimum fair share. We use the maximum fair share achieved in order to limit the input rate of those flows which crosses the bottleneck links contention area when the flows that are not allocated to the optimal transmission rate and calculate the following highest fair share. Through simulation results, we show that the proposed protocol achieves improved fair share and throughput with reduced delay.

Keywords: MAC-layer, MANETs, Multihop, optimal rate, Transmission.

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2044 Switched Reluctance Generator for Wind Power Applications

Authors: M. Nassereddine, J. Rizk, M. Nagrial

Abstract:

Green house effect has becomes a serious concern in many countries due to the increase consumption of the fossil fuel. There have been many studies to find an alternative power source. Wind energy found to be one of the most useful solutions to help in overcoming the air pollution and global. There is no agreed solution to conversion of wind energy to electrical energy. In this paper, the advantages of using a Switched Reluctance Generator (SRG) for wind energy applications. The theoretical study of the self excitation of a SRG and the determination of the variable parameters in a SRG design are discussed. The design parameters for the maximum power output of the SRG are computed using Matlab simulation. The designs of the circuit to control the variable parameters in a SRG to provide the maximum power output are also discussed.

Keywords: Switched Reluctance Generator, Wind Power, Electrical Machines.

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2043 Landfill Leachate: A Promising Substrate for Microbial Fuel Cells

Authors: Jayesh M. Sonawane, Prakash C. Ghosh

Abstract:

Landfill leachate emerges as a promising feedstock for microbial fuel cells (MFCs). In the present investigation, direct air-breathing cathode-based MFCs are fabricated to investigate the potential of landfill leachate. Three MFCs that have different cathode areas are fabricated and investigated for 17 days under open circuit conditions. The maximum open circuit voltage (OCV) is observed to be as high as 1.29 V. The maximum cathode area specific power density achieved in the reactor is 1513 mW m-2. Further studies are under progress to understand the origin of high OCV obtained from landfill leachate-based MFCs.

Keywords: Microbial fuel cells, landfill leachate, air-breathing cathode, performance study.

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2042 Elastic-Plastic Analysis for Finite Deformation of a Rotating Disk Having Variable Thickness with Inclusion

Authors: Sanjeev Sharma, Manoj Sahni

Abstract:

Transition theory has been used to derive the elasticplastic and transitional stresses. Results obtained have been discussed numerically and depicted graphically. It is observed that the rotating disk made of incompressible material with inclusion require higher angular speed to yield at the internal surface as compared to disk made of compressible material. It is seen that the radial and circumferential stresses are maximum at the internal surface with and without edge load (for flat disk). With the increase in thickness parameter (k = 2, 4), the circumferential stress is maximum at the external surface while the radial stress is maximum at the internal surface. From the figures drawn the disk with exponentially varying thickness (k = 2), high angular speed is required for initial yielding at internal surface as compared to flat disk and exponentially varying thickness for k = 4 onwards. It is concluded that the disk made of isotropic compressible material is on the safer side of the design as compared to disk made of isotropic incompressible material as it requires higher percentage increase in an angular speed to become fully plastic from its initial yielding.

Keywords: Finite deformation, Incompressibility, Transitionalstresses, Elastic-plastic.

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2041 Performance Evaluation of an ANC-based Hybrid Algorithm for Multi-target Wideband Active Sonar Echolocation System

Authors: Jason Chien-Hsun Tseng

Abstract:

This paper evaluates performances of an adaptive noise cancelling (ANC) based target detection algorithm on a set of real test data supported by the Defense Evaluation Research Agency (DERA UK) for multi-target wideband active sonar echolocation system. The hybrid algorithm proposed is a combination of an adaptive ANC neuro-fuzzy scheme in the first instance and followed by an iterative optimum target motion estimation (TME) scheme. The neuro-fuzzy scheme is based on the adaptive noise cancelling concept with the core processor of ANFIS (adaptive neuro-fuzzy inference system) to provide an effective fine tuned signal. The resultant output is then sent as an input to the optimum TME scheme composed of twogauge trimmed-mean (TM) levelization, discrete wavelet denoising (WDeN), and optimal continuous wavelet transform (CWT) for further denosing and targets identification. Its aim is to recover the contact signals in an effective and efficient manner and then determine the Doppler motion (radial range, velocity and acceleration) at very low signal-to-noise ratio (SNR). Quantitative results have shown that the hybrid algorithm have excellent performance in predicting targets- Doppler motion within various target strength with the maximum false detection of 1.5%.

Keywords: Wideband Active Sonar Echolocation, ANC Neuro-Fuzzy, Wavelet Denoise, CWT, Hybrid Algorithm.

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2040 Extending the Quantum Entropy to Multidimensional Signal Processing

Authors: Youssef Khmou, Said Safi, Miloud Frikel

Abstract:

This paper treats different aspects of entropy measure in classical information theory and statistical quantum mechanics, it presents the possibility of extending the definition of Von Neumann entropy to image and array processing. In the first part, we generalize the quantum entropy using singular values of arbitrary rectangular matrices to measure the randomness and the quality of denoising operation, this new definition of entropy can be implemented to compare the performance analysis of filtering methods. In the second part, we apply the concept of pure state in quantum formalism to generalize the maximum entropy method for narrowband and farfield source localization problem. Several computer simulation results are illustrated to demonstrate the effectiveness of the proposed techniques.

Keywords: Von Neumann entropy, Filtering, array, DoA, Maximum Entropy Method.

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2039 Offline Parameter Identification and State-of-Charge Estimation for Healthy and Aged Electric Vehicle Batteries Based on the Combined Model

Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

Abstract:

Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: Lithium-Ion batteries, genetic algorithm optimization, battery aging test, and parameter identification.

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2038 Evaluation of Expected Annual Loss Probabilities of RC Moment Resisting Frames

Authors: Saemee Jun, Dong-Hyeon Shin, Tae-Sang Ahn, Hyung-Joon Kim

Abstract:

Building loss estimation methodologies which have been advanced considerably in recent decades are usually used to estimate socio and economic impacts resulting from seismic structural damage. In accordance with these methods, this paper presents the evaluation of an annual loss probability of a reinforced concrete moment resisting frame designed according to Korean Building Code. The annual loss probability is defined by (1) a fragility curve obtained from a capacity spectrum method which is similar to a method adopted from HAZUS, and (2) a seismic hazard curve derived from annual frequencies of exceedance per peak ground acceleration. Seismic fragilities are computed to calculate the annual loss probability of a certain structure using functions depending on structural capacity, seismic demand, structural response and the probability of exceeding damage state thresholds. This study carried out a nonlinear static analysis to obtain the capacity of a RC moment resisting frame selected as a prototype building. The analysis results show that the probability of being extensive structural damage in the prototype building is expected to 0.01% in a year.

Keywords: Expected annual loss, Loss estimation, RC structure, Fragility analysis.

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2037 Roles of Aquatic Plants on Erosion Relief of Stream Bed

Authors: Jin-Hong Kim

Abstract:

Roles of the vegetation to mitigate the erosion of the stream bed or to facilitate the deposition of the fine sediments by the species of the aquatic plants were presented. Field investigation on the estimation of the change of the bed level and the estimation of the flow characteristics were performed. The results showed that Phragmites japonica has the mitigation function of 0.3m-0.4m of the erosion in the range of higher than 1.0m/s of flow velocity at the vegetated region. Phragmites communis has the mitigation function of 0.2m-0.3m of the erosion in the range of higher than 0.7m/s of flow velocity at the vegetated region. Salix gracilistyla has greater role than Phragmites japonica and Phragmites communis to sustain the stable channel. It has the mitigation function of 0.4m-0.5m of the erosion in the range of higher than 1.4m/s of flow velocity. Miscanthus sacchariflorus has a weak role compared with that of Phragmites japonica and Salix gracilistyla, but it has still function for sustaining the stable bed. From these results, the vegetation has effective roles to mitigate the erosion or to facilitate the deposition of the stream bed.

Keywords: Aquatic plants, Phragmites japonica, Phragmites communis, Miscanthus sacchariflorus, Salix gracilistyla.

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2036 Energy Management System in HEV Using PI Controller

Authors: S. Saravanan, G. Sugumaran

Abstract:

Nowadays the use of Hybrid Electric Vehicles (HEV) is increasing dramatically. The HEV is mainly dependent on electricity and there is always a need for storage of charge. Fuel Cell (FC), Batteries and Ultra Capacitor are being used for the proposed HEV as an electric power source or as an energy storage unit. The aim of developing an energy management technique is to utilize the sources according to the requirement of the vehicle with help of controller. This increases the efficiency of hybrid electric vehicle to reduce the fuel consumption and unwanted emission. The Maximum Power Point Tracking (MPPT) in FC is done using (Perturb & Observe) algorithm. In this paper, the control of automobiles at variable speed is achieved effectively.

Keywords: Batteries, Energy Management System (EMS), Fuel Cell (FC), Hybrid Electric Vehicles (HEVs), Maximum Power Point Tracking (MPPT).

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2035 Stochastic Scheduling to Minimize Expected Lateness in Multiple Identical Machines

Authors: Ghulam Zakria, Zailin Guan , Yasser Riaz Awan, Wan Lizhi

Abstract:

There are many real world problems in which parameters like the arrival time of new jobs, failure of resources, and completion time of jobs change continuously. This paper tackles the problem of scheduling jobs with random due dates on multiple identical machines in a stochastic environment. First to assign jobs to different machine centers LPT scheduling methods have been used, after that the particular sequence of jobs to be processed on the machine have been found using simple stochastic techniques. The performance parameter under consideration has been the maximum lateness concerning the stochastic due dates which are independent and exponentially distributed. At the end a relevant problem has been solved using the techniques in the paper..

Keywords: Quantity Production Flow Shop, LPT Scheduling, Stochastic Scheduling, Maximum Lateness, Random Due Dates

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2034 A Novel Receiver Algorithm for Coherent Underwater Acoustic Communications

Authors: Liang Zhao, Jianhua Ge

Abstract:

In this paper, we proposed a novel receiver algorithm for coherent underwater acoustic communications. The proposed receiver is composed of three parts: (1) Doppler tracking and correction, (2) Time reversal channel estimation and combining, and (3) Joint iterative equalization and decoding (JIED). To reduce computational complexity and optimize the equalization algorithm, Time reversal (TR) channel estimation and combining is adopted to simplify multi-channel adaptive decision feedback equalizer (ADFE) into single channel ADFE without reducing the system performance. Simultaneously, the turbo theory is adopted to form joint iterative ADFE and convolutional decoder (JIED). In JIED scheme, the ADFE and decoder exchange soft information in an iterative manner, which can enhance the equalizer performance using decoding gain. The simulation results show that the proposed algorithm can reduce computational complexity and improve the performance of equalizer. Therefore, the performance of coherent underwater acoustic communications can be improved greatly.

Keywords: Underwater acoustic communication, Time reversal (TR) combining, joint iterative equalization and decoding (JIED)

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2033 Scour Depth Prediction around Bridge Piers Using Neuro-Fuzzy and Neural Network Approaches

Authors: H. Bonakdari, I. Ebtehaj

Abstract:

The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN and ANFIS methods via dimensional analysis, and subsequently, the parameters are predicted. In the current study, the methods’ performances are compared with the nonlinear regression (NLR) method. The results show that both methods presented in this study outperform existing methods. Moreover, using the ratio of pier length to flow depth, ratio of median diameter of particles to flow depth, ratio of pier width to flow depth, the Froude number and standard deviation of bed grain size parameters leads to optimal performance in scour depth estimation.

Keywords: Adaptive neuro-fuzzy inference system, ANFIS, artificial neural network, ANN, bridge pier, scour depth, nonlinear regression, NLR.

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2032 Studies on the Feasibility of Cow’s Urine as Non-Conventional Energy Sources

Authors: Raj Kumar Rajak, Bharat Mishra

Abstract:

Bio-batteries represent an entirely new long-term, reasonable, reachable, and eco-friendly approach to generation of sustainable energy. In the present experimental work, we have studied the effect of the generation of power by bio-battery using different electrode pairs. The tests show that it is possible to generate electricity using cow’s urine as an electrolyte. C-Mg electrode pair shows maximum Voltage and Short Circuit Current (SCC), while C-Zn electrode pair shows less Open Circuit Voltage (OCV) and SCC. By the studies of cow urine and different electrodes, it is found that C-Zn electrode battery is more economical. The cow urine battery with C-Zn electrode provides maximum power (707.4 mW) and durability (up to 145 h). This result shows that the bio-batteries have the potency to full fill the need of electricity demand for lower energy equipment.

Keywords: Bio-batteries, cow’s urine, electrodes, non-conventional.

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2031 Analysis of Translational Ship Oscillations in a Realistic Environment

Authors: Chen Zhang, Bernhard Schwarz-Röhr, Alexander Härting

Abstract:

To acquire accurate ship motions at the center of gravity, a single low-cost inertial sensor is utilized and applied on board to measure ship oscillating motions. As observations, the three axes accelerations and three axes rotational rates provided by the sensor are used. The mathematical model of processing the observation data includes determination of the distance vector between the sensor and the center of gravity in x, y, and z directions. After setting up the transfer matrix from sensor’s own coordinate system to the ship’s body frame, an extended Kalman filter is applied to deal with nonlinearities between the ship motion in the body frame and the observation information in the sensor’s frame. As a side effect, the method eliminates sensor noise and other unwanted errors. Results are not only roll and pitch, but also linear motions, in particular heave and surge at the center of gravity. For testing, we resort to measurements recorded on a small vessel in a well-defined sea state. With response amplitude operators computed numerically by a commercial software (Seaway), motion characteristics are estimated. These agree well with the measurements after processing with the suggested method.

Keywords: Extended Kalman filter, nonlinear estimation, sea trial, ship motion estimation.

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2030 An Effect of Organic Supplements on Stimulating Growth of Vanda and Mokara Seedlings in Tissue Culture

Authors: Kullanart Obsuwan, Chockpisit Thepsithar

Abstract:

This study aimed to investigate effect of different organic supplements on growth of Vanda and Mokara seedlings. Vanda and Mokara seedlings approximately 0.2 and 0.3 cm. in height were sub-cultured onto VW supplemented with 150 ml/L coconut water, 100 g/L potato extract, 100 g/L ‘Gros Michel’ banana (AAA group) and 100 g/L ‘Namwa’ banana (ABB group). The explants were sub-cultured onto the same medium every month for 3 months. The best medium increased stem height to 0.52 and 0.44 Cm. in Vanda and Mokara respectively was supplemented with coconut water. The maximum fresh weight of Vanda (0.59 g) was found on medium supplemented with ‘Gros Michel’ banana while Mokara cultured on medium supplemented with Potato extract had the maximum fresh weight (0.27 g) and number of roots (5.20 roots/shoot) statistically different (p≤ 0.05) to other treatments. However, Vanda cultured on medium supplemented with ‘Namwa’ banana had the maximum number of roots (3.80 roots/shoot). Our results suggested that growth of different orchid genera was responded diversely to different organic supplements. 

 

Keywords: Fresh weight, in vitro propagation, orchid, plant height.

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2029 Estimation of Time -Varying Linear Regression with Unknown Time -Volatility via Continuous Generalization of the Akaike Information Criterion

Authors: Elena Ezhova, Vadim Mottl, Olga Krasotkina

Abstract:

The problem of estimating time-varying regression is inevitably concerned with the necessity to choose the appropriate level of model volatility - ranging from the full stationarity of instant regression models to their absolute independence of each other. In the stationary case the number of regression coefficients to be estimated equals that of regressors, whereas the absence of any smoothness assumptions augments the dimension of the unknown vector by the factor of the time-series length. The Akaike Information Criterion is a commonly adopted means of adjusting a model to the given data set within a succession of nested parametric model classes, but its crucial restriction is that the classes are rigidly defined by the growing integer-valued dimension of the unknown vector. To make the Kullback information maximization principle underlying the classical AIC applicable to the problem of time-varying regression estimation, we extend it onto a wider class of data models in which the dimension of the parameter is fixed, but the freedom of its values is softly constrained by a family of continuously nested a priori probability distributions.

Keywords: Time varying regression, time-volatility of regression coefficients, Akaike Information Criterion (AIC), Kullback information maximization principle.

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2028 The Role of Velocity Map Quality in Estimation of Intravascular Pressure Distribution

Authors: Ali Pashaee, Parisa Shooshtari, Gholamreza Atae, Nasser Fatouraee

Abstract:

Phase-Contrast MR imaging methods are widely used for measurement of blood flow velocity components. Also there are some other tools such as CT and Ultrasound for velocity map detection in intravascular studies. These data are used in deriving flow characteristics. Some clinical applications are investigated which use pressure distribution in diagnosis of intravascular disorders such as vascular stenosis. In this paper an approach to the problem of measurement of intravascular pressure field by using velocity field obtained from flow images is proposed. The method presented in this paper uses an algorithm to calculate nonlinear equations of Navier- Stokes, assuming blood as an incompressible and Newtonian fluid. Flow images usually suffer the lack of spatial resolution. Our attempt is to consider the effect of spatial resolution on the pressure distribution estimated from this method. In order to achieve this aim, velocity map of a numerical phantom is derived at six different spatial resolutions. To determine the effects of vascular stenoses on pressure distribution, a stenotic phantom geometry is considered. A comparison between the pressure distribution obtained from the phantom and the pressure resulted from the algorithm is presented. In this regard we also compared the effects of collocated and staggered computational grids on the pressure distribution resulted from this algorithm.

Keywords: Flow imaging, pressure distribution estimation, phantom, resolution.

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2027 Modeling and Design of MPPT Controller Using Stepped P&O Algorithm in Solar Photovoltaic System

Authors: R. Prakash, B. Meenakshipriya, R. Kumaravelan

Abstract:

This paper presents modeling and simulation of Grid Connected Photovoltaic (PV) system by using improved mathematical model. The model is used to study different parameter variations and effects on the PV array including operating temperature and solar irradiation level. In this paper stepped P&O algorithm is proposed for MPPT control. This algorithm will identify the suitable duty ratio in which the DC-DC converter should be operated to maximize the power output. Photo voltaic array with proposed stepped P&O-MPPT controller can operate in the maximum power point for the whole range of solar data (irradiance and temperature).

Keywords: Photovoltaic (PV), Maximum Power Point Tracking (MPPT), Boost converter, Stepped Perturb & Observe method (Stepped P&O).

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2026 Model Predictive Control with Unscented Kalman Filter for Nonlinear Implicit Systems

Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

A class of implicit systems is known as a more generalized class of systems than a class of explicit systems. To establish a control method for such a generalized class of systems, we adopt model predictive control method which is a kind of optimal feedback control with a performance index that has a moving initial time and terminal time. However, model predictive control method is inapplicable to systems whose all state variables are not exactly known. In other words, model predictive control method is inapplicable to systems with limited measurable states. In fact, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. It is also usual that output signals are disturbed by process and sensor noises. Hence, it is important to establish a state estimation method for nonlinear implicit systems with taking the process noise and sensor noise into consideration. To this purpose, we apply the model predictive control method and unscented Kalman filter for solving the optimization and estimation problems of nonlinear implicit systems, respectively. The objective of this study is to establish a model predictive control with unscented Kalman filter for nonlinear implicit systems.

Keywords: Model predictive control, unscented Kalman filter, nonlinear systems, implicit systems.

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2025 The Estimate Rate of Permanent Flow of a Liquid Simulating Blood by Doppler Effect

Authors: Malika.D Kedir-Talha, Mohammed Mehenni

Abstract:

To improve the characterization of blood flows, we propose a method which makes it possible to use the spectral analysis of the Doppler signals. Our calculation induces a reasonable approximation, the error made on estimated speed reflects the fact that speed depends on the flow conditions as well as on measurement parameters like the bore and the volume flow rate. The estimate of the Doppler signal frequency enables us to determine the maximum Doppler frequencie Fd max as well as the maximum flow speed. The results show that the difference between the estimated frequencies ( Fde ) and the Doppler frequencies ( Fd ) is small, this variation tends to zero for important θ angles and it is proportional to the diameter D. The description of the speed of friction and the coefficient of friction justify the error rate obtained.

Keywords: Doppler frequency, Doppler spectrum, estimate speed, permanent flow.

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2024 Assessment of Nickel Concentration in Surface and Ground Water of the Kowsar Dam Basin

Authors: Fardin Boustani, M Hojati , S Ebrahimzadeh

Abstract:

The Kowsar dam supply water for different usages such as drinking, industrial, agricultural and aquaculture farms usages and located next to the city of Dehdashat in Kohgiluye and Boyerahmad province in southern Iran. There are some towns and villages on the Kowsar dam watersheds, which Dehdasht and Choram are the most important and populated cities in this area. The study was undertaken to assess the status of water quality in the urban areas of the Kowsar dam. A total of 28 water samples were collected from 6 stations on surface water and 1 station from groundwater on the watershed of the Kowsar dam. All the samples were analyzed for Ni concentration using standard procedures. The results were compared with other national and international standards. Among the analyzed samples, as the maximum value of Nickel (0.01 mg/L) was observed on the station 2 at the autumn 2010, all the samples analyzed were within the maximum admissible limits by the United States Environmental Protection Agency, EU, WHO and the Iranian. In general results of the present study have shown that a Ni mean value of station No. 2 with 0.006 mg/L is higher than the other stations. Ni level of all samples and stations have had normal values and this is an indication of pollution potential and hazards because of human activity and waste water of towns in the areas, which can effect on human health implications in future. This research, therefore, recommends the government and other responsible authorities to take suitable improving measures in the Kowsar dam watersheds.

Keywords: Kowsar dam, Drinking water quality, Nickel, Maximum admissible limit, World health organization

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2023 Skin Detection using Histogram depend on the Mean Shift Algorithm

Authors: Soo- Young Ye, Ki-Gon Nam, Ki-Won Byun

Abstract:

In this paper, we were introduces a skin detection method using a histogram approximation based on the mean shift algorithm. The proposed method applies the mean shift procedure to a histogram of a skin map of the input image, generated by comparison with standard skin colors in the CbCr color space, and divides the background from the skin region by selecting the maximum value according to brightness level. The proposed method detects the skin region using the mean shift procedure to determine a maximum value that becomes the dividing point, rather than using a manually selected threshold value, as in existing techniques. Even when skin color is contaminated by illumination, the procedure can accurately segment the skin region and the background region. The proposed method may be useful in detecting facial regions as a pretreatment for face recognition in various types of illumination.

Keywords: Skin region detection, mean shift, histogram approximation.

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2022 Fuzzy Control of the Air Conditioning System at Different Operating Pressures

Authors: Mohanad Alata , Moh'd Al-Nimr, Rami Al-Jarrah

Abstract:

The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.

Keywords: Air Conditioning, ANFIS, Fuzzy Control, Sugeno System.

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2021 A Data Driven Approach for the Degradation of a Lithium-Ion Battery Based on Accelerated Life Test

Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

Abstract:

Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: Accelerated life test, inverse power law, lithium ion battery, reliability evaluation, Weibull distribution.

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2020 Complex Condition Monitoring System of Aircraft Gas Turbine Engine

Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

Abstract:

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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2019 Strain Based Evaluation of Dents in Pressurized Pipes

Authors: Maziar Ramezani, Thomas Neitzert

Abstract:

A dent is a gross distortion of the pipe cross-section. Dent depth is defined as the maximum reduction in the diameter of the pipe compared to the original diameter. Pipeline dent finite element (FE) simulation and theoretical analysis are conducted in this paper to develop an understanding of the geometric characteristics and strain distribution in the pressurized dented pipe. Based on the results, the magnitude of the denting force increases significantly with increasing the internal pressure, and the maximum circumferential and longitudinal strains increase by increasing the internal pressure and the dent depth. The results can be used for characterizing dents and ranking their risks to the integrity of a pipeline.

Keywords: dented steel pipelines, Finite element model, Internal pressure, Strain distribution

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