Search results for: optical model parameters

Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: Satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization.

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Authors: Agata Kowalska, Radosław K. Kowalski, Zdzisław Zakęś

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Our results showed that treatment with both cyclooxygenase (COX1 or COX2) inhibitors impair reproduction parameters of the medaka. Resveratrol (COX1 inhibitor) caused an decrease in the number of spawning females at the first week of feeding fish with experimental diets. In the group treated with NS- 398 (COX2 inhibitor) we found the lowest sperm velocity parameters and decreased linearity of movement. The ovaries of the medaka fed feed supplemented with Resveratrol or NS-398 were confirmed to have a lower share of matured oocytes however during the experiment (four weeks) the number of eggs spawned by females was similar. Both inhibitors in fish diet (20 mg/kg body weight/day) caused a decrease in the embryo survival. Our results revealed that for the medaka female reproduction, activity of both COX enzymes might be necessary whereas males reproduction competence, as expressed by sperm motility parameters, might be related to COX2 activity.

Keywords: COX innibitors, medaka, reproduction parameters

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Authors: Mamta Agrawal, Neeru Adlakha, K.R. Pardasani

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An attempt has been made to develop a seminumerical model to study temperature variations in dermal layers of human limbs. The model has been developed for two dimensional steady state case. The human limb has been assumed to have elliptical cross section. The dermal region has been divided into three natural layers namely epidermis, dermis and subdermal tissues. The model incorporates the effect of important physiological parameters like blood mass flow rate, metabolic heat generation, and thermal conductivity of the tissues. The outer surface of the limb is exposed to the environment and it is assumed that heat loss takes place at the outer surface by conduction, convection, radiation, and evaporation. The temperature of inner core of the limb also varies at the lower atmospheric temperature. Appropriate boundary conditions have been framed based on the physical conditions of the problem. Cubic splines approach has been employed along radial direction and Fourier series along angular direction to obtain the solution. The numerical results have been computed for different values of eccentricity resembling with the elliptic cross section of the human limbs. The numerical results have been used to obtain the temperature profile and to study the relationships among the various physiological parameters.

Keywords: Blood Mass Flow Rate, Metabolic Heat Generation, Fourier Series, Cubic splines and Thermal Conductivity.

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Authors: Kazuyoshi Mori

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In this paper, we consider the parametrization of the discrete-time systems without the unit-delay element within the framework of the factorization approach. In the parametrization, we investigate the number of required parameters. We consider single-input single-output systems in this paper. By the investigation, we find, on the discrete-time systems without the unit-delay element, three cases that are (1) there exist plants which require only one parameter and (2) two parameters, and (3) the number of parameters is at most three.

Keywords: Linear systems, parametrization, Coprime Factorization, number of parameters.

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Authors: Muhammad Rizwan Azhar, Emadadeen Ali

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In this paper, periodic force operation of a wastewater treatment process has been studied for the improved process performance. A previously developed dynamic model for the process is used to conduct the performance analysis. The static version of the model was utilized first to determine the optimal productivity conditions for the process. Then, feed flow rate in terms of dilution rate i.e. (D) is transformed into sinusoidal function. Nonlinear model predictive control algorithm is utilized to regulate the amplitude and period of the sinusoidal function. The parameters of the feed cyclic functions are determined which resulted in improved productivity than the optimal productivity under steady state conditions. The improvement in productivity is found to be marginal and is satisfactory in substrate conversion compared to that of the optimal condition and to the steady state condition, which corresponds to the average value of the periodic function. Successful results were also obtained in the presence of modeling errors and external disturbances.

Keywords: Dilution rate, nonlinear model predictive control, sinusoidal function, wastewater treatment.

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Authors: Chang Liu, John Nash, Stephen D. Prior

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This paper presents the design and implementation details of a complete unmanned aerial system (UAS) based on commercial-off-the-shelf (COTS) components, focusing on safety, security, search and rescue scenarios in GPS-denied environments. In particular, The aerial platform is capable of semi-autonomously navigating through extremely low-light, GPS-denied indoor environments based on onboard sensors only, including a downward-facing optical flow camera. Besides, an additional low-cost payload camera system is developed to stream both infra-red video and visible light video to a ground station in real-time, for the purpose of detecting sign of life and hidden humans. The total cost of the complete system is estimated to be $1150, and the effectiveness of the system has been tested and validated in practical scenarios.

Keywords: Unmanned aerial system, commercial-off-the-shelf, extremely low-light, GPS-denied, optical flow, infrared video.

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Authors: Yue Hu, Xilu Zhao, Takao Yamaguchi, Manabu Sasajima, Yoshio Koike, Akira Hara

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This study optimized the design parameters of a cone loudspeaker as an example of high flexibility of the product design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to optimize each parameter of the loudspeaker design. To overcome the limitation of the design problem in practice, this study presents an acoustic analysis algorithm to optimize the design parameters of the loudspeaker. The material character of cone paper and the loudspeaker edge were the design parameters, and the vibration displacement of the cone paper was the objective function. The results of the analysis showed that the design had high accuracy as compared to the predicted value. These results suggested that although the parameter design is difficult, with experience and intuition, the design can be performed easily using the optimized design found with the acoustic analysis software.

Keywords: Air viscosity, design parameters, loudspeaker, optimization.

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Authors: K. Easawi, M. Nabil, T. Abdallah, S. Negm, H. Talaat

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Composite nanostructures of metal core/semiconductor shell (Au/CdS) configuration were prepared using organometalic method. UV-Vis spectra for the Au/CdS colloids show initially two well separated bands, corresponding to surface plasmon of the Au core, and the exciton of CdS shell. The absorption of CdS shell is enhanced, while the Au plasmon band is suppressed as the shell thickness increases. The shell sizes were estimated from the optical spectra using the effective mass approximation model (EMA), and compared to the sizes of the Au core and CdS shell measured by high resolution transmission electron microscope (HRTEM). The changes in the absorption features are discussed in terms of gradual increase in the coupling strength of the Au core surface plasmon and the exciton in the CdS. leading to charge transfer and modification of electron oscillation in Au core.

Keywords: Nanocomposites, Plasmonics.

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Authors: F.Belhocine-Nemmar; MS.Belkaid D. Hatem, O Boughias

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In this work, the influence of temperature on the different parameters of solar cells based on organic semiconductors are studied. The short circuit current Isc increases so monotonous with temperature and then saturates to a maximum value before decreasing at high temperatures. The open circuit voltage Vco decreases linearly with temperature. The fill factor FF and efficiency, which are directly related with Isc and Vco follow the variations of the letters. The phenomena are explained by the behaviour of the mobility which is a temperature activated process.

Keywords: cells parameters, organic materials, solar cells, temperature effect

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Authors: Hadj Bourdoucen, Adel Gastli

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In this paper, an approach for finding optimized layouts for connecting PV units delivering maximum array output power is suggested. The approach is based on considering the different varying parameters of PV units that might be extracted from a general two-diode model. These are mainly, solar irradiation, reverse saturation currents, ideality factors, series and shunt resistances in addition to operating temperature. The approach has been tested on 19 possible 2×3 configurations and allowed to determine the optimized configurations as well as examine the effects of the different units- parameters on the maximum output power. Thus, using this approach, standard arrays with n×m units can be configured for maximum generated power and allows designing PV based systems having reduced surfaces to fit specific required power, as it is the case for solar cars and other mobile systems.

Keywords: Photovoltaic, PV unit, optimum configuration, maximum power, Orcad.

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Authors: S. Chonsatidjamroen , K-N. Areerak, K-L. Areerak

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This paper presents the averaging model of a buck converter derived from the generalized state-space averaging method. The sliding mode control is used to regulate the output voltage of the converter and taken into account in the model. The proposed model requires the fast computational time compared with those of the full topology model. The intensive time-domain simulations via the exact topology model are used as the comparable model. The results show that a good agreement between the proposed model and the switching model is achieved in both transient and steady-state responses. The reported model is suitable for the optimal controller design by using the artificial intelligence techniques.

Keywords: Generalized state-space averaging method, buck converter, sliding mode control, modeling, simulation.

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Authors: E. Assareh, M.A. Behrang, M. Ghalambaz, A.R. Noghrehabadi, A. Ghanbarzadeh

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In this paper, a new approach is introduced to solve Blasius equation using parameter identification of a nonlinear function which is used as approximation function. Bees Algorithm (BA) is applied in order to find the adjustable parameters of approximation function regarding minimizing a fitness function including these parameters (i.e. adjustable parameters). These parameters are determined how the approximation function has to satisfy the boundary conditions. In order to demonstrate the presented method, the obtained results are compared with another numerical method. Present method can be easily extended to solve a wide range of problems.

Keywords: Bees Algorithm (BA); Approximate Solutions; Blasius Differential Equation.

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Authors: Mohanad Alata, Mohammad Molhim, Abdullah Ramini

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Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models.

Keywords: Fuzzy clustering, Fuzzy C-Means, Genetic Algorithm, Sugeno fuzzy systems.

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Authors: D. Kari Basavaraja, M. G. Skanda, C. Soumya, V. Ramesh

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This paper discusses the effects of sodium hypophosphite concentration, pH, and temperature on deposition rate. This paper also discusses the evaluation of coating strength, surface, and subsurface by varying the bath parameters, percentage of phosphate, plating temperature, and pH of the plating solution. Taguchi technique has been used for the analysis. In the experiment, nickel chloride which is a source of nickel when mixed with sodium hypophosphite has been used as the reducing agent and the source of phosphate and sodium hydroxide has been used to vary the pH of the coating bath. The coated samples are tested for impact energy by conducting impact test. Finally, the effects of coating bath parameters on the impact energy absorbed have been plotted, and analysis has been carried out. Further, percentage contribution of coating bath parameters using Design of Experiments approach (DOE) has been analysed. Finally, it can be concluded that the bath parameters of the Ni-P coating will certainly influence on the strength of the specimen.

Keywords: Bath parameters, coatings, design of experiment, fracture toughness, impact strength.

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Artificial Intelligence (AI), specifically Reinforcement Learning (RL), has proven helpful in many control path planning technologies by maximizing and enhancing their performance, such as navigation systems. Since it learns from experience by interacting with the environment to determine the optimal policy, the optimal policy takes the best action in a particular state, accounting for the long-term rewards. Most navigation systems focus primarily on "arriving faster," overlooking safety and efficiency while estimating the optimum path, as safety and efficiency are essential factors when planning for a long-distance journey. This paper represents an RL control model that proposes a control mechanism for improving navigation systems. Also, the model could be applied to other control path planning applications because it is adjustable and can accept different properties and parameters. However, the navigation system application has been taken as a case and evaluation study for the proposed model. The model utilized a Q-learning algorithm for training and updating the policy. It allows the agent to analyze the quality of an action made in the environment to maximize rewards. The model gives the ability to update rewards regularly based on safety and efficiency assessments, allowing the policy to consider the desired safety and efficiency benefits while making decisions, which improves the quality of the decisions taken for path planning compared to the conventional RL approaches.

Keywords: Artificial intelligence, control system, navigation systems, reinforcement learning.

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Authors: Naoto Suzuki

Abstract:

Japanese are affected by the most common causes of eyesight loss such as glaucoma, diabetic retinopathy, pigmentary retinal degeneration, and age-related macular degeneration. We developed an ophthalmological examination apparatus with a fundus camera, precisely fundus-related perimetry (microperimetry), and electroretinogram (ERG) functions to diagnose a variety of diseases that cause eyesight loss. The experimental apparatus was constructed with the same optical system as a fundus camera. The microperimetry optical system was calculated and added to the experimental apparatus using the German company Optenso's optical engineering software (OpTaliX-LT 10.8). We also added an Edmund infrared camera (EO-0413), a lens with a 25 mm focal length, a 45° cold mirror, a 12 V/50 W halogen lamp, and an 8-inch monitor. We made the artificial eye of a plane-convex lens, a black spacer, and a hemispherical cup. The hemispherical cup had a small section of the paper at the bottom. The artificial eye was photographed five times using the experimental apparatus. The software was created to display the examination target on the monitor and save examination data using C++Builder 10.2. The retinal fundus was displayed on the monitor at a length and width of 1 mm and a resolution of 70.4 ± 4.1 and 74.7 ± 6.8 pixels, respectively. The microperimetry and ERG functions were successfully added to the experimental ophthalmological apparatus. A moving machine was developed to measure the artificial eye's movement. The artificial eye's rear part was painted black and white in the central area. It was rotated 10 degrees from one side to the other. The movement was captured five times as motion videos. Three static images were extracted from one of the motion videos captured. The images display the artificial eye facing the center, right, and left directions. The three images were processed using Scilab 6.1.0 and Image Processing and Computer Vision Toolbox 4.1.2, including trimming, binarization, making a window, deleting peripheral area, and morphological operations. To calculate the artificial eye's fundus center, we added a gravity method to the program to calculate the gravity position of connected components. From the three images, the image processing could calculate the center position.

Keywords: Ophthalmological examination apparatus, microperimetry, electroretinogram, eye movement.

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Authors: Romain Bosquet, Pierre-Olivier Vandanjon, Alex Coiret, Tristan Lorino

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In the hardening energy context, the transport sector which constitutes a large worldwide energy demand has to be improving for decrease energy demand and global warming impacts. In a controversial situation where subsists an increasing demand for long-distance and high-speed travels, high-speed trains offer many advantages, as consuming significantly less energy than road or air transports. At the project phase of new rail infrastructures, it is nowadays important to characterize accurately the energy that will be induced by its operation phase, in addition to other more classical criteria as construction costs and travel time. Current literature consumption models used to estimate railways operation phase are obsolete or not enough accurate for taking into account the newest train or railways technologies. In this paper, an updated model of consumption for high-speed is proposed, based on experimental data obtained from full-scale tests performed on a new high-speed line. The assessment of the model is achieved by identifying train parameters and measured power consumptions for more than one hundred train routes. Perspectives are then discussed to use this updated model for accurately assess the energy impact of future railway infrastructures.

Keywords: High-speed train, energy, model, track profile, infrastructure

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Authors: Reza Bazargan Lari, Mohammad H. Fattahi

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Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.

Keywords: Wavelet, de-noising, predictability, time series fractal analysis, valid length, ANN.

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Authors: Kamyar Shameli, Mansor Bin Ahmad, Wan Md Zin Wan Yunus, Nor Azowa Ibrahim, Maryam Jokar, Majid Darroudi

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Silver/polylactide nanocomposites (Ag/PLA-NCs) were synthesized via chemical reduction method in diphase solvent. Silver nitrate and sodium borohydride were used as a silver precursor and reducing agent in the polylactide (PLA). The properties of Ag/PLA-NCs were studied as a function of the weight percentages of silver nanoparticles (8, 16 and 32 wt% of Ag-NPs) relative to the weight of PLA. The Ag/PLA-NCs were characterized by Xray diffraction (XRD), transmission electron microscopy (TEM), electro-optical microscopy (EOM), UV-visible spectroscopy (UV-vis) and Fourier transform infrared spectroscopy (FT-IR). XRD patterns confirmed that Ag-NPs crystallographic planes were face centered cubic (fcc) type. TEM images showed that mean diameters of Ag-NPs were 3.30, 3.80 and 4.80 nm. Electro-optical microscopy revealed excellent dispersion and interaction between Ag-NPs and PLA films. The generation of silver nanoparticles was confirmed from the UVvisible spectra. FT-IR spectra showed that there were no significant differences between PLA and Ag/PLA-NCs films. The synthesized Ag/PLA-NCs were stable in organic solution over a long period of time without sign of precipitation.

Keywords: Nanocomposites, Polylactide, Silver Nanoparticles, Sodium Borohydride, Transmission Electron Microscopy.

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Authors: Ahmad Aljaafreh

Abstract:

This paper proposes a hierarchical hidden Markov model (HHMM) to model the detection of M vehicles in a wireless sensor network (WSN). The HHMM model contains an extra level of hidden Markov model to model the temporal transitions of each state of the first HMM. By modeling the temporal transitions, only those hypothesis with nonzero transition probabilities needs to be tested. Thus, this method efficiently reduces the computation load, which is preferable in WSN applications.This paper integrates several techniques to optimize the detection performance. The output of the states of the first HMM is modeled as Gaussian Mixture Model (GMM), where the number of states and the number of Gaussians are experimentally determined, while the other parameters are estimated using Expectation Maximization (EM). HHMM is used to model the sequence of the local decisions which are based on multiple hypothesis testing with maximum likelihood approach. The states in the HHMM represent various combinations of vehicles of different types. Due to the statistical advantages of multisensor data fusion, we propose a heuristic based on fuzzy weighted majority voting to enhance cooperative classification of moving vehicles within a region that is monitored by a wireless sensor network. A fuzzy inference system weighs each local decision based on the signal to noise ratio of the acoustic signal for target detection and the signal to noise ratio of the radio signal for sensor communication. The spatial correlation among the observations of neighboring sensor nodes is efficiently utilized as well as the temporal correlation. Simulation results demonstrate the efficiency of this scheme.

Keywords: Classification, decision fusion, fuzzy logic, hidden Markov model

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Authors: Yi-Chang Chen, Shan-Lin Chang, Chia-Chun Wu

Abstract:

Unlike this study focused extensively on trading behavior of option market, those researches were just taken their attention to model-driven option pricing. For example, Black-Scholes (B-S) model is one of the most famous option pricing models. However, the arguments of B-S model are previously mentioned by some pricing models reviewing. This paper following suggests the importance of the dynamic character for option pricing, which is also the reason why using the genetic algorithm (GA). Because of its natural selection and species evolution, this study proposed a hybrid model, the Genetic-BS model which combining GA and B-S to estimate the price more accurate. As for the final experiments, the result shows that the output estimated price with lower MAE value than the calculated price by either B-S model or its enhanced one, Gram-Charlier garch (G-C garch) model. Finally, this work would conclude that the Genetic-BS pricing model is exactly practical.

Keywords: genetic algorithm, Genetic-BS, option pricing model.

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Authors: Hadi Adibi-Asl, Alireza Doosthosseini, Amir Taghavipour

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This paper studies the design of an adaptive control strategy to tune an active steering system for better drivability and maneuverability. In the first step, adaptive control strategy is applied to estimate the uncertain parameters on-line (e.g. cornering stiffness), then the estimated parameters are fed into the pole placement controller to generate corrective feedback gain to improve the steering system dynamic’s characteristics. The simulations are evaluated for three types of road conditions (dry, wet, and icy), and the performance of the adaptive pole placement control (APPC) are compared with pole placement control (PPC) and a passive system. The results show that the APPC strategy significantly improves the yaw rate and side slip angle of a bicycle plant model.

Keywords: Adaptive control, active steering, pole placement, vehicle dynamics.

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Authors: Sunita Dhingra, Satinder Bal Gupta, Ranjit Biswas

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Multiprocessor task scheduling is a NP-hard problem and Genetic Algorithm (GA) has been revealed as an excellent technique for finding an optimal solution. In the past, several methods have been considered for the solution of this problem based on GAs. But, all these methods consider single criteria and in the present work, minimization of the bi-criteria multiprocessor task scheduling problem has been considered which includes weighted sum of makespan & total completion time. Efficiency and effectiveness of genetic algorithm can be achieved by optimization of its different parameters such as crossover, mutation, crossover probability, selection function etc. The effects of GA parameters on minimization of bi-criteria fitness function and subsequent setting of parameters have been accomplished by central composite design (CCD) approach of response surface methodology (RSM) of Design of Experiments. The experiments have been performed with different levels of GA parameters and analysis of variance has been performed for significant parameters for minimisation of makespan and total completion time simultaneously.

Keywords: Multiprocessor task scheduling, Design of experiments, Genetic Algorithm, Makespan, Total completion time.

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

Abstract:

Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.

Keywords: Enhanced ideal gas molecular movement, Kriging, probability-based damage detection, probability of damage existence, surrogate modeling, uncertainty quantification.

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Authors: Alexander Urbach, Mukharbij Banov, Vladislav Turko

Abstract:

Fatigue tests of specimen-s with numerous holes are presented. The tests were made up till fatigue cracks have been created on both sides of the hole. Their extension was stopping with pressed plastic deformation at the mouth of the detected crack. It is shown that the moments of occurrence of cracks on holes are stochastically dependent. This dependence has positive and negative correlation relations. Shown that the positive correlation is formed across of the applied force, while negative one – along it. The negative relationship extends over a greater distance. The mathematical model of dependence area formation is represented as well as the estimating of model parameters. The positive correlation of fatigue cracks origination can be considered as an extension of one main crack. With negative correlation the first crack locates the place of its origin, leading to the appearance of multiple cracks; do not merge with each other.

Keywords: Correlation analysis, fatigue damage accumulation, local area, mathematical model.

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Authors: Louis Denis Kevin Catherine, Raja Aziz Raja Ma’arof, Azrina Arshad, Sangeeth Suresh

Abstract:

Machining parameters are very important in determining the surface quality of any material. In the past decade, some new engineering materials were developed for the manufacturing industry which created a need to conduct an investigation on the impact of the said parameters on their surface roughness. Polyurethane (PU) block is widely used in the automotive industry to manufacture parts such as checking fixtures that are used to verify the dimensional accuracy of automotive parts. In this paper, the design of experiment (DOE) was used to investigate on the effect of the milling parameters on the PU block. Furthermore, an analysis of the machined surface chemical composition was done using scanning electron microscope (SEM). It was found that the surface roughness of the PU block is severely affected when PU undergoes a flood machining process instead of a dry condition. In addition the stepover and the silicon content were found to be the most significant parameters that influence the surface quality of the PU block.

Keywords: Polyurethane (PU), design of experiment (DOE), scanning electron microscope (SEM), surface roughness.

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Authors: Z. Rihova, K. Saksl, C. Siemers, D. Ostroushko

Abstract:

Titanium alloys like the modern alloy Ti 6Al 2Sn 4Zr 6Mo (Ti-6246) combine excellent specific mechanical properties and corrosion resistance. On the other hand,due to their material characteristics, machining of these alloys is difficult to perform. The aim of the current study is the analyses of wear mechanisms of coated cemented carbide tools applied in orthogonal cutting experiments of Ti-6246 alloy. Round bars were machined with standard coated tools in dry conditions on a CNC latheusing a wide range of cutting speeds and cutting depths. Tool wear mechanisms were afterwards investigated by means of stereo microscopy, optical microscopy, confocal microscopy and scanning electron microscopy. Wear mechanisms included fracture of the tool tip (total failure) and abrasion. Specific wear features like crater wear, micro cracks and built-up edgeformation appeared depending of the mechanical and thermal conditions generated in the workpiece surface by the cutting action.

Keywords: Alloy 6246, machining, tool wear, optical microscopy, SEM, EDX analysis

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Authors: Rashmi S. H., G. M. Madhu, A. A. Kittur, R. Suresh

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Polymer nanocomposites represent a new class of materials in which nanomaterials act as the reinforcing material in composites, wherein small additions of nanomaterials lead to large enhancements in thermal, optical and mechanical properties. A boost in these properties is due to the large interfacial area per unit volume or weight of the nanoparticles and the interactions between the particle and the polymer. Micro sized particles used as reinforcing agents scatter light, thus reducing light transmittance and optical clarity. Efficient nanoparticle dispersion combined with good polymer–particle interfacial adhesion eliminates scattering and allows the exciting possibility of developing strong yet transparent films, coatings and membranes. This paper aims at synthesising zinc oxide nanoparticles which are reinforced in poly vinyl alcohol (PVA) polymer. The mechanical properties showed that the tensile strength of the PVA nanocomposites increases with the increase in the amount of nanoparticles.

Keywords: Glutaraldehyde, polymer nanocomposites, poly vinyl alcohol, zinc oxide.

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Authors: L. Dzierzbicka-Głowacka, M. Janecki

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Dynamic of phytoplankton blooms in the Baltic Sea has been analyzed applying the numerical ecosystem model 3D CEMBS. The model consists of the hydrodynamic model (POP, version 2.1) and the ice model (CICE, version 4.0), which are imposed by the atmospheric data model (DATM7). The 3D model has an ecosystem module, activated in 2012 in the operational mode. The ecosystem model consists of 11 main variables: biomass of small-size phytoplankton and large-size phytoplankton and cyanobacteria, zooplankton biomass, dissolved and molecular detritus, dissolved oxygen concentration, as well as concentrations of nutrients, including: nitrates, ammonia, phosphates and silicates. The 3D-CEMBS model is an effective tool for solving problems related to phytoplankton blooms dynamic in the Baltic Sea

Keywords: Ecosystem model, phytoplankton, Baltic Sea

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Authors: Jianqiao. Yu, Jianbo. Wang, Xinzhen. He

Abstract:

This paper presents a longitudinal quasi-linear model for the ADMIRE model. The ADMIRE model is a nonlinear model of aircraft flying in the condition of high angle of attack. So it can-t be considered to be a linear system approximately. In this paper, for getting the longitudinal quasi-linear model of the ADMIRE, a state transformation based on differentiable functions of the nonscheduling states and control inputs is performed, with the goal of removing any nonlinear terms not dependent on the scheduling parameter. Since it needn-t linear approximation and can obtain the exact transformations of the nonlinear states, the above-mentioned approach is thought to be appropriate to establish the mathematical model of ADMIRE. To verify this conclusion, simulation experiments are done. And the result shows that this quasi-linear model is accurate enough.

Keywords: quasi-linear model, simulation, state transformation approach, the ADMIRE model.

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