Search results for: simple linear regression analysis

Authors: S. Raissi

Abstract:

Response surface methodology (RSM) is a very efficient tool to provide a good practical insight into developing new process and optimizing them. This methodology could help engineers to raise a mathematical model to represent the behavior of system as a convincing function of process parameters. Through this paper the sequential nature of the RSM surveyed for process engineers and its relationship to design of experiments (DOE), regression analysis and robust design reviewed. The proposed four-step procedure in two different phases could help system analyst to resolve the parameter design problem involving responses. In order to check accuracy of the designed model, residual analysis and prediction error sum of squares (PRESS) described. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with one or more responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.

Keywords: Response Surface Methodology (RSM), Design of Experiments (DOE), Process modeling, Process setting, Process optimization.

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Authors: Tawiwat Veeraklaew, Nathasit Phathana-im, Songkit Heama

Abstract:

Both the minimum energy consumption and smoothness, which is quantified as a function of jerk, are generally needed in many dynamic systems such as the automobile and the pick-and-place robot manipulator that handles fragile equipments. Nevertheless, many researchers come up with either solely concerning on the minimum energy consumption or minimum jerk trajectory. This research paper proposes a simple yet very interesting relationship between the minimum direct and indirect jerks approaches in designing the time-dependent system yielding an alternative optimal solution. Extremal solutions for the cost functions of direct and indirect jerks are found using the dynamic optimization methods together with the numerical approximation. This is to allow us to simulate and compare visually and statistically the time history of control inputs employed by minimum direct and indirect jerk designs. By considering minimum indirect jerk problem, the numerical solution becomes much easier and yields to the similar results as minimum direct jerk problem.

Keywords: Optimization, Dynamic, Linear Systems, Jerks.

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Authors: A. Muthuramalingam, S. Himavathi

Abstract:

Harmonic pollution and low power factor in power systems caused by power converters have been of great concern. To overcome these problems several converter topologies using advanced semiconductor devices and control schemes have been proposed. This investigation is to identify a low cost, small size, efficient and reliable ac to dc converter to meet the input performance index of UPS. The performance of single phase and three phase ac to dc converter along with various control techniques are studied and compared. The half bridge converter topology with linear current control is identified as most suitable. It is simple, energy efficient because of single switch power loss and transformer-less operation of UPS. The results are validated practically using a prototype built using IGBT and analog controller. The performance for both single and three-phase system is verified. Digital implementation of closed loop control achieves higher reliability. Its cost largely depends on chosen bit precision. The minimal bit precision for optimum converter performance is identified as 16-bit with fixed-point operation. From the investigation and practical implementation it is concluded that half bridge ac – dc converter along with digital linear controller meets the performance index of UPS for single and three phase systems.

Keywords: PFC, energy efficient, half bridge, ac-dc converter, boost topology, linear current control, digital bit precision.

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Authors: V. Tawiwat, P. Jumnong

Abstract:

Both the minimum energy consumption and smoothness, which is quantified as a function of jerk, are generally needed in many dynamic systems such as the automobile and the pick-and-place robot manipulator that handles fragile equipments. Nevertheless, many researchers come up with either solely concerning on the minimum energy consumption or minimum jerk trajectory. This research paper proposes a simple yet very interesting when combining the minimum energy and jerk of indirect jerks approaches in designing the time-dependent system yielding an alternative optimal solution. Extremal solutions for the cost functions of the minimum energy, the minimum jerk and combining them together are found using the dynamic optimization methods together with the numerical approximation. This is to allow us to simulate and compare visually and statistically the time history of state inputs employed by combining minimum energy and jerk designs. The numerical solution of minimum direct jerk and energy problem are exactly the same solution; however, the solutions from problem of minimum energy yield the similar solution especially in term of tendency.

Keywords: Optimization, Dynamic, Linear Systems, Jerks.

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Authors: Mikail Altan

Abstract:

International trust takes first place in the development of foreign trade in the country. They see an important role in ensuring that trust. Various payment methods that are developed in the banking system provide fast and reliable way to execution and promote foreign trade by financing the foreign trade. In this study, we investigate the influence of bank on foreign trade in Turkey. 26 years of data for 1990-2015 period have been used in this study. After correlation analysis, a simple regression model was established. Payment methods that are developed in the banking system make a positive contribution in Turkey’s foreign trade volume. In addition, the export of Turkey was affected positively more than import’s by these payment methods.

Keywords: Banks, export, foreign trade, import.

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Authors: Watcharapan Sukkerd, Teeradej Wuttipornpun

Abstract:

This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.

Keywords: Capacitated MRP, non-population search algorithms, linear programming, assembly flow shop.

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Authors: Karima Siham Aoubid, Mohamed Boulemden

Abstract:

The development of the signal compression algorithms is having compressive progress. These algorithms are continuously improved by new tools and aim to reduce, an average, the number of bits necessary to the signal representation by means of minimizing the reconstruction error. The following article proposes the compression of Arabic speech signal by a hybrid method combining the wavelet transform and the linear prediction. The adopted approach rests, on one hand, on the original signal decomposition by ways of analysis filters, which is followed by the compression stage, and on the other hand, on the application of the order 5, as well as, the compression signal coefficients. The aim of this approach is the estimation of the predicted error, which will be coded and transmitted. The decoding operation is then used to reconstitute the original signal. Thus, the adequate choice of the bench of filters is useful to the transform in necessary to increase the compression rate and induce an impercevable distortion from an auditive point of view.

Keywords: Compression, linear prediction analysis, multiresolution analysis, speech signal.

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Authors: Montri Phothisonothai, Masahiro Nakagawa

Abstract:

The objective of this paper is to characterize the spontaneous Electroencephalogram (EEG) signals of four different motor imagery tasks and to show hereby a possible solution for the present binary communication between the brain and a machine ora Brain-Computer Interface (BCI). The processing technique used in this paper was the fractal analysis evaluated by the Critical Exponent Method (CEM). The EEG signal was registered in 5 healthy subjects,sampling 15 measuring channels at 1024 Hz.Each channel was preprocessed by the Laplacian space ltering so as to reduce the space blur and therefore increase the spaceresolution. The EEG of each channel was segmented and its Fractaldimension (FD) calculated. The FD was evaluated in the time interval corresponding to the motor imagery and averaged out for all the subjects (each channel). In order to characterize the FD distribution,the linear regression curves of FD over the electrodes position were applied. The differences FD between the proposed mental tasks are quantied and evaluated for each experimental subject. The obtained results of the proposed method are a substantial fractal dimension in the EEG signal of motor imagery tasks and can be considerably utilized as the multiple-states BCI applications.

Keywords: electroencephalogram (EEG), motor imagery tasks, mental tasks, biomedical signals processing, human-machine interface, fractal analysis, critical exponent method (CEM).

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Authors: Amiel Satvedi, Richard Pyne

Abstract:

Injuries in professional sports occur on a regular basis. Some may be minor while others can cause huge impact on a player’s career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player’s number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.

Keywords: Injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer.

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Authors: F. Khaber, K. Zehar, A. Hamzaoui

Abstract:

In this paper, we introduce a robust state feedback controller design using Linear Matrix Inequalities (LMIs) and guaranteed cost approach for Takagi-Sugeno fuzzy systems. The purpose on this work is to establish a systematic method to design controllers for a class of uncertain linear and non linear systems. Our approach utilizes a certain type of fuzzy systems that are based on Takagi-Sugeno (T-S) fuzzy models to approximate nonlinear systems. We use a robust control methodology to design controllers. This method not only guarantees stability, but also minimizes an upper bound on a linear quadratic performance measure. A simulation example is presented to show the effectiveness of this method.

Keywords: Takagi-Sugeno fuzzy model, state feedback, linear matrix inequalities, robust stability.

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

Abstract:

Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.

Keywords: Identification of a technical condition, aviation gasturbine engine, fuzzy logic and neural networks.

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Authors: Jelena S. Kiurski, Vesna S. Kecić, Snežana M. Aksentijević

Abstract:

The identification and evaluation of organic and inorganic pollutants were performed in a flexographic facility in Novi Sad, Serbia. Air samples were collected and analyzed in situ, during 4-hours working time at five sampling points by the mobile gas chromatograph and ozonometer at the printing of collagen casing. Experimental results showed that the concentrations of isopropyl alcohol, acetone, total volatile organic compounds and ozone varied during the sampling times. The highest average concentrations of 94.80 ppm and 102.57 ppm were achieved at 200 minutes from starting the production for isopropyl alcohol and total volatile organic compounds, respectively. The mutual dependences between target hazardous and microclimate parameters were confirmed using a multiple linear regression model with software package STATISTICA 10. Obtained multiple coefficients of determination in the case of ozone and acetone (0.507 and 0.589) with microclimate parameters indicated a moderate correlation between the observed variables. However, a strong positive correlation was obtained for isopropyl alcohol and total volatile organic compounds (0.760 and 0.852) with microclimate parameters. Higher values of parameter F than F_critical for all examined dependences indicated the existence of statistically significant difference between the concentration levels of target pollutants and microclimates parameters. Given that, the microclimate parameters significantly affect the emission of investigated gases and the application of eco-friendly materials in production process present a necessity.

Keywords: Flexographic printing, indoor air, multiple regression analysis, pollution emission.

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

Abstract:

Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.

Keywords: Identification of a technical condition, aviation gasturbine engine, fuzzy logic and neural networks.

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Authors: C. S. Wong, K. H. Badri, N. Ataollahi, K. P. Law, M. S. Su’ait, N. I. Hassan

Abstract:

Novel bio-based polymer electrolyte was synthesized with LiClO4 as the main source of charge carrier. Initially, polyurethane-LiClO4 polymer electrolytes were synthesized via prepolymerization method with different NCO/OH ratios and labelled them as PU1, PU2, PU3 and PU4. Fourier transform infrared (FTIR) analysis indicates the co-ordination between Li+ ion and polyurethane in PU1. Differential scanning calorimetry (DSC) analysis indicates PU1 has the highest glass transition temperature (Tg) corresponds to the most abundant urethane group which is the hard segment in PU1. Scanning electron microscopy (SEM) shows the good miscibility between lithium salt and the polymer. The study found that PU1 possessed the greatest ionic conductivity and the lowest activation energy, Ea. All the polyurethanes exhibited linear Arrhenius variations indicating ion transport via simple lithium ion hopping in polyurethane. This research proves the NCO content in polyurethane plays an important role in affecting the ionic conductivity of this polymer electrolyte.

Keywords: Ionic conductivity, Palm kernel oil-based monoester polyol, polyurethane, solid polymer electrolyte.

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Authors: Adriano Z. Zambom, Preethi Ravikumar

Abstract:

One of the biggest challenges in nonparametric regression is the curse of dimensionality. Additive models are known to overcome this problem by estimating only the individual additive effects of each covariate. However, if the model is misspecified, the accuracy of the estimator compared to the fully nonparametric one is unknown. In this work the efficiency of completely nonparametric regression estimators such as the Loess is compared to the estimators that assume additivity in several situations, including additive and non-additive regression scenarios. The comparison is done by computing the oracle mean square error of the estimators with regards to the true nonparametric regression function. Then, a backward elimination selection procedure based on the Akaike Information Criteria is proposed, which is computed from either the additive or the nonparametric model. Simulations show that if the additive model is misspecified, the percentage of time it fails to select important variables can be higher than that of the fully nonparametric approach. A dimension reduction step is included when nonparametric estimator cannot be computed due to the curse of dimensionality. Finally, the Boston housing dataset is analyzed using the proposed backward elimination procedure and the selected variables are identified.

Keywords: Additive models, local polynomial regression, residuals, mean square error, variable selection.

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Authors: E. Ansari-Piri, N. Eghbali

Abstract:

Let A and B be two linear algebras. A linear map ϕ : A → B is called an n-homomorphism if ϕ(a1...an) = ϕ(a1)...ϕ(an) for all a1, ..., an ∈ A. In this note we have a verification on the behavior of almost n-multiplicative linear maps with n > 2 in the fuzzy normed spaces

Keywords: Almost multiplicative maps, n-homomorphism maps, almost n-multiplicative maps, fuzzy normed space, stability.

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Authors: Musthaya Patchanee

Abstract:

This research aimed to study form of traffic distribution and environmental factors of road that affect traffic accidents in Dusit District, only areas responsible of Samsen Police Station. Data used in this analysis is the secondary data of traffic accident case from year 2011. Observed area units are 15 traffic lines that are under responsible of Samsen Police Station. Technique and method used are the Cartographic Method, the Correlation Analysis, and the Multiple Regression Analysis. The results of form of traffic accidents show that, the Samsen Road area had most traffic accidents (24.29%), second was Rachvithi Road(18.10%), third was Sukhothai Road (15.71%), fourth was Rachasrima Road (12.38%), and fifth was Amnuaysongkram Road(7.62%). The result from Dusit District, onlyareasresponsibleofSamsen police station, has suggested that the scale of accidents have high positive correlation with statistic significant at level 0.05 and the frequency of travel (r=0.857). Traffic intersection point (r=0.763)and traffic control equipments (r=0.713) are relevant factors respectively. By using the Multiple Regression Analysis, travel frequency is the only one that has considerable influences on traffic accidents in Dusit district only Samsen Police Station area. Also, a factor in frequency of travel can explain the change in traffic accidents scale to 73.40 (R² = 0.734). By using the Multiple regression summation from analysis was Ŷ=-7.977+0.044X6

Keywords: Form of Traffic Distribution, Environmental Factors of road, Traffic Accidents, Dusit District.

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Authors: Hassam Ahmed, Yuanzhi Liu, Yassine Selami, Wei Tao, Hui Zhao

Abstract:

The purpose of this research is to develop a real time axial force measurement system for a smart bearing through the use of strain-gauges, whereby the data acquisition is performed by an Arduino microcontroller due to its easy manipulation and low-cost. The measured signal is acquired and then discretized using a Wheatstone Bridge and an Analog-Digital Converter (ADC) respectively. For bearing monitoring, a real time monitoring system based on Internet of things (IoT) and Bluetooth were developed. Experimental tests were performed on a bearing within a force range up to 600 kN. The experimental results show that there is a proportional linear relationship between the applied force and the output voltage, and the error R squared is within 0.9878 based on the regression analysis.

Keywords: Bearing, force measurement, IoT, strain gauge.

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Authors: Kreangkri Ratchagit

Abstract:

This paper is concerned with exponential stability and stabilization of switched linear systems with interval time-varying delays. The time delay is any continuous function belonging to a given interval, in which the lower bound of delay is not restricted to zero. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton-s formula, a switching rule for the exponential stability and stabilization of switched linear systems with interval time-varying delays and new delay-dependent sufficient conditions for the exponential stability and stabilization of the systems are first established in terms of LMIs. Numerical examples are included to illustrate the effectiveness of the results.

Keywords: Switching design, exponential stability and stabilization, switched linear systems, interval delay, Lyapunov function, linear matrix inequalities.

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Authors: L. J. de Bessa Neto, V. S. Filho, J. V. Ferreira Nunes, G. C. Bergamo

Abstract:

There are many situations in which human activities have significant effects on the environment. Damage to the ozone layer is one of them. The objective of this work is to use the Least Squares Method, considering the linear, exponential, logarithmic, power and polynomial models of the second degree, to analyze through the coefficient of determination (R²), which model best fits the behavior of the chlorodifluoromethane (HCFC-142b) in parts per trillion between 1992 and 2018, as well as estimates of future concentrations between 5 and 10 periods, i.e. the concentration of this pollutant in the years 2023 and 2028 in each of the adjustments. A total of 809 observations of the concentration of HCFC-142b in one of the monitoring stations of gases precursors of the deterioration of the ozone layer during the period of time studied were selected and, using these data, the statistical software Excel was used for make the scatter plots of each of the adjustment models. With the development of the present study, it was observed that the logarithmic fit was the model that best fit the data set, since besides having a significant R² its adjusted curve was compatible with the natural trend curve of the phenomenon.

Keywords: Chlorodifluoromethane (HCFC-142b), ozone (O3), least squares method, regression models.

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Authors: Chutarat Boontho

Abstract:

The purposes of this study were as follows to evaluate the economic value of Phu Kradueng National Park by the travel cost method (TCM) and the contingent valuation method (CVM) and to estimate the demand for traveling and the willingness to pay. The data for this study were collected by conducting two large scale surveys on users and non-users. A total of 1,016 users and 1,034 non-users were interviewed. The data were analyzed using multiple linear regression analysis, logistic regression model and the consumer surplus (CS) was the integral of demand function for trips. The survey found, were as follows: 1)Using the travel cost method which provides an estimate of direct benefits to park users, we found that visitors- total willingness to pay per visit was 2,284.57 bath, of which 958.29 bath was travel cost, 1,129.82 bath was expenditure for accommodation, food, and services, and 166.66 bath was consumer surplus or the visitors -net gain or satisfaction from the visit (the integral of demand function for trips). 2) Thai visitors to Phu Kradueng National Park were further willing to pay an average of 646.84 bath per head per year to ensure the continued existence of Phu Kradueng National Park and to preserve their option to use it in the future. 3) Thai non-visitors, on the other hand, are willing to pay an average of 212.61 bath per head per year for the option and existence value provided by the Park. 4) The total economic value of Phu Kradueng National Park to Thai visitors and non-visitors taken together stands today at 9,249.55 million bath per year. 5) The users- average willingness to pay for access to Phu Kradueng National Park rises from 40 bath to 84.66 bath per head per trip for improved services such as road improvement, increased cleanliness, and upgraded information. This paper was needed to investigate of the potential market demand for bio prospecting in Phu Kradueng national Park and to investigate how a larger share of the economic benefits of tourism could be distributed income to the local residents.

Keywords: Contingent Valuation Method, Travel Cost Method, Consumer surplus.

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Authors: Jonathan H. Perez, Fumihiko Tanaka, Daisuke Hamanaka, Toshitaka Uchino

Abstract:

A finite element analysis was conducted to determine the effect of moisture diffusion and hygroscopic swelling in rice. A parallel simple stochastic modeling was performed to predict the number of grains cracked as a result of moisture absorption and hygroscopic swelling. Rice grains were soaked in thermally (25 oC) controlled water and then tested for compressive stress. The destructive compressive stress tests revealed through compressive stress calculation that the peak force required to cause cracking in grains soaked in water reduced with time as soaking duration was extended. Results of the experiment showed that several grains had their value of the predicted compressive stress below the von Mises stress and were interpreted as grains which become cracked and/or broke during soaking. The technique developed in this experiment will facilitate the approximation of the number of grains which will crack during soaking.

Keywords: Cracking, Finite element analysis, hygroscopic swelling, moisture diffusion, von Mises stress.

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Authors: Xin Kai, Juan Li, Sexin Huang, Zengliang Bai

Abstract:

Ethanol is generally used as a therapeutic reagent against Hepatocellular carcinoma (HCC or hepatoma) worldwide, as it can induce Hepatocellular carcinoma cell apoptosis at low concentration through a multifactorial process regulated by several unknown proteins. This paper provides a simple and available proteomic strategy for exploring differentially expressed proteins in the apoptotic pathway. The appropriate concentrations of ethanol required to induce HepG2 cell apoptosis were first assessed by MTT assay, Gisma and fluorescence staining. Next, the central proteins involved in the apoptosis pathway processs were determined using 2D-PAGE, SDS-PAGE, and bio-software analysis. Finally the downregulation of two proteins, AFP and survivin, were determined by immunocytochemistry and reverse transcriptase PCR (RT-PCR) technology. The simple, useful method demonstrated here provides a new approach to proteomic analysis in key bio-regulating process including proliferation, differentiation, apoptosis, immunity and metastasis.

Keywords: Hepatocellular carcinoma, Ethanol, Proteomics, survivin and AFP

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Authors: G. Parmar, S. Mukherjee, R. Prasad

Abstract:

The authors present an optimization algorithm for order reduction and its application for the determination of the relative mapping errors of linear time invariant dynamic systems by the simplified models. These relative mapping errors are expressed by means of the relative integral square error criterion, which are determined for both unit step and impulse inputs. The reduction algorithm is based on minimization of the integral square error by particle swarm optimization technique pertaining to a unit step input. The algorithm is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. Two numerical examples are solved to illustrate the superiority of the algorithm over some existing methods.

Keywords: Order reduction, Particle swarm optimization, Relative mapping error, Stability.

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Authors: Amir Azizi, Amir Yazid b. Ali, Loh Wei Ping, Mohsen Mohammadzadeh

Abstract:

Uncertainties of a serial production line affect on the production throughput. The uncertainties cannot be prevented in a real production line. However the uncertain conditions can be controlled by a robust prediction model. Thus, a hybrid model including autoregressive integrated moving average (ARIMA) and multiple polynomial regression, is proposed to model the nonlinear relationship of production uncertainties with throughput. The uncertainties under consideration of this study are demand, breaktime, scrap, and lead-time. The nonlinear relationship of production uncertainties with throughput are examined in the form of quadratic and cubic regression models, where the adjusted R-squared for quadratic and cubic regressions was 98.3% and 98.2%. We optimized the multiple quadratic regression (MQR) by considering the time series trend of the uncertainties using ARIMA model. Finally the hybrid model of ARIMA and MQR is formulated by better adjusted R-squared, which is 98.9%.

Keywords: ARIMA, multiple polynomial regression, production throughput, uncertainties

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Authors: Abdullah A. AlShaher

Abstract:

In this paper, we demonstrate how regression curves can be used to recognize 2D non-rigid handwritten shapes. Each shape is represented by a set of non-overlapping uniformly distributed landmarks. The underlying models utilize 2^nd order of polynomials to model shapes within a training set. To estimate the regression models, we need to extract the required coefficients which describe the variations for a set of shape class. Hence, a least square method is used to estimate such modes. We then proceed by training these coefficients using the apparatus Expectation Maximization algorithm. Recognition is carried out by finding the least error landmarks displacement with respect to the model curves. Handwritten isolated Arabic characters are used to evaluate our approach.

Keywords: Shape recognition, Arabic handwritten characters, regression curves, expectation maximization algorithm.

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Authors: H. Alaleh, N. Hedayat, A. Alaleh, H. Ayazi, A. Ruhani

Abstract:

Run-offs are considered as important hydrological factors in feasibility studies of river engineering and irrigation-related projects under arid and semi-arid condition. Flood control is one of the crucial factor, the management of which while mitigates its destructive consequences, abstracts considerable volume of renewable water resources. The methodology applied here was based on Mizumura, which applied a mathematical model for simple tank to simulate the rainfall-run-off process in a particular water basin using the data from the observational hydrograph. The model was applied in the Dez River water basin adjacent to Greater Dezful region, Iran in order to simulate and estimate the floods. Results indicated that the calculated hydrographs using the simple tank method, SCS-CN model and the observation hydrographs had a close proximity. It was also found that on average the flood time and discharge peaks in the simple tank were closer to the observational data than the CN method. On the other hand, the calculated flood volume in the CN model was significantly closer to the observational data than the simple tank model.

Keywords: Simple tank, Dez River, run-off, lag time, excess rainfall.

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Authors: El-Said Badr, Mahmoud Moussa, Konstantinos Paparrizos, Nikolaos Samaras, Angelo Sifaleras

Abstract:

There are two major variants of the Simplex Algorithm: the revised method and the standard, or tableau method. Today, all serious implementations are based on the revised method because it is more efficient for sparse linear programming problems. Moreover, there are a number of applications that lead to dense linear problems so our aim in this paper is to present some computational results on parallel implementation of dense Simplex Method. Our implementation is implemented on a SMP cluster using C programming language and the Message Passing Interface MPI. Preliminary computational results on randomly generated dense linear programs support our results.

Keywords: Linear Programming, MPI, Parallel Implementation, Simplex Algorithm.

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Authors: Hong Dongchen, Chen Qiuxiao, Wu Shuang

Abstract:

Systematic Science reveals the complex nonlinear mechanisms of behavior in urban system. However, when confronted with such system, most city planners in China are still utilizing simple linear thinking to learn and understand this open complex giant system. In this paper, the hypercycle theory was introduced, which is one of the basis theories of systematic science. Based on the analysis of the reasons for the failure of current urban planning in China, and in consideration of the nonlinear characteristics of the urban system as well, optimization ideas for urban planning formulation were presented such as the shift from blueprint planning to progressive planning and from the rigid urban planning management control to its dynamically monitor and in time feedback.

Keywords: Systematic science, hypercycle theory, urban planning.

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Authors: Hazem M. Al-Mofleh, John E. Daniels, Joseph W. McKean

Abstract:

In this paper numerous robust fitting procedures are considered in estimating spatial variograms. In spatial statistics, the conventional variogram fitting procedure (non-linear weighted least squares) suffers from the same outlier problem that has plagued this method from its inception. Even a 3-parameter model, like the variogram, can be adversely affected by a single outlier. This paper uses the Hogg-Type adaptive procedures to select an optimal score function for a rank-based estimator for these non-linear models. Numeric examples and simulation studies will demonstrate the robustness, utility, efficiency, and validity of these estimates.

Keywords: Asymptotic relative efficiency, non-linear rank-based, robust, rank estimates, variogram.

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