Search results for: linear machine

Authors: E. Ardil, Erdem Uçar, Parvinder S. Sandhu

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As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done on time especially for the critical applications. In this paper, we have explored the different predictor models to NASA-s public domain defect dataset coded in Perl programming language. Different machine learning algorithms belonging to the different learner categories of the WEKA project including Mamdani Based Fuzzy Inference System and Neuro-fuzzy based system have been evaluated for the modeling of maintenance severity or impact of fault severity. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provides relatively better prediction accuracy as compared to other models and hence, can be used for the maintenance severity prediction of the software.

Keywords: Software Metrics, Fuzzy, Neuro-Fuzzy, SoftwareFaults, Accuracy, MAE, RMSE.

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Authors: G. Mesfin, M. Shuhaimi

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This paper proposes a new optimization techniques for the optimization a gas processing plant uncertain feed and product flows. The problem is first formulated using a continuous linear deterministic approach. Subsequently, the single and joint chance constraint models for steady state process with timedependent uncertainties have been developed. The solution approach is based on converting the probabilistic problems into their equivalent deterministic form and solved at different confidence levels Case study for a real plant operation has been used to effectively implement the proposed model. The optimization results indicate that prior decision has to be made for in-operating plant under uncertain feed and product flows by satisfying all the constraints at 95% confidence level for single chance constrained and 85% confidence level for joint chance constrained optimizations cases.

Keywords: Butane, Feed composition, LPG, Productspecification, Propane.

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Authors: Weifeng Wang, Xilong Chen, Xianwei Zeng

Abstract:

The cable tower of Liede Bridge is a double-column curved-lever arched-beam portal framed structure. Being novel and unique in structure, its cable tower differs in complexity from traditional ones. This paper analyzes the ultimate load capacity of cable tower by adopting the finite element calculations and model tests which indicate that constitutive relations applied here give a better simulation of actual failure process of prestressed reinforced concrete. In vertical load, horizontal load and overloading tests, the stepped loading of the tower model is of linear relationship, and the test data has good repeatability. All suggests that the cable tower has good bearing capacity, rational design and high emergency capacity.

Keywords: Cable tower of Liede Bridge, ultimate load capacity, model test, nonlinear finite element method

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Authors: Roza Dastres, Mohsen Soori

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Digital Signal Processing (DSP) is the use of digital processing systems by computers in order to perform a variety of signal processing operations. It is the mathematical manipulation of a digital signal's numerical values in order to increase quality as well as effects of signals. DSP can include linear or nonlinear operators in order to process and analyze the input signals. The nonlinear DSP processing is closely related to nonlinear system detection and can be implemented in time, frequency and space-time domains. Applications of the DSP can be presented as control systems, digital image processing, biomedical engineering, speech recognition systems, industrial engineering, health care systems, radar signal processing and telecommunication systems. In this study, advanced methods and different applications of DSP are reviewed in order to move forward the interesting research filed.

Keywords: Digital signal processing, advanced telecommunication, nonlinear signal processing, speech recognition systems.

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Authors: Koray U. Erbas

Abstract:

Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: Convolutional Neural Network, Deep Learning, Deep Learning Based FER, Facial Emotion Recognition.

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Authors: Mohammadsadegh Zanganehfar

Abstract:

Since the introduction of fractal geometry in 1970, numerous efforts have been made by architects and researchers to transfer this area of mathematical knowledge in the discipline of architecture and postmodernist discourse. The discourse of complexity and architecture is one of the most significant ongoing discourses in the discipline of architecture from the 70's until today and has generated significant styles such as deconstructivism and parametricism in architecture. During these years, several projects were designed and presented by designers and architects using fractal geometry, but due to the lack of sufficient knowledge and appropriate comprehension of the features and characteristics of this nonlinear geometry, none of the fractal-based designs have been successful and satisfying. Fractal geometry as a geometric technology has a long presence in the history of architecture. The current research attempts to identify and discover the characteristics, features, potentials and functionality of fractals despite their aesthetic aspect by examining case studies of pre-modern architecture in Asia and investigating the function of fractals. 

Keywords: Asian architecture, fractal geometry, fractal technique, geometric properties

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Authors: K. S. Chia, H. Abdul Rahim, R. Abdul Rahim

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The Principal component regression (PCR) is a combination of principal component analysis (PCA) and multiple linear regression (MLR). The objective of this paper is to revise the use of PCR in shortwave near infrared (SWNIR) (750-1000nm) spectral analysis. The idea of PCR was explained mathematically and implemented in the non-destructive assessment of the soluble solid content (SSC) of pineapple based on SWNIR spectral data. PCR achieved satisfactory results in this application with root mean squared error of calibration (RMSEC) of 0.7611 Brix°, coefficient of determination (R2) of 0.5865 and root mean squared error of crossvalidation (RMSECV) of 0.8323 Brix° with principal components (PCs) of 14.

Keywords: Pineapple, Shortwave near infrared, Principal component regression, Non-invasive measurement; Soluble solids content

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Authors: Mogari I. Rapoo, Diteboho Xaba

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This paper examines the forecasting performance of Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN) models with the published exchange rate obtained from South African Reserve Bank (SARB). ARIMA is one of the popular linear models in time series forecasting for the past decades. ARIMA and ANN models are often compared and literature revealed mixed results in terms of forecasting performance. The study used the MSE and MAE to measure the forecasting performance of the models. The empirical results obtained reveal the superiority of ARIMA model over ANN model. The findings further resolve and clarify the contradiction reported in literature over the superiority of ARIMA and ANN models.

Keywords: ARIMA, artificial neural networks models, error metrics, exchange rates.

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Authors: Thashmee Karunaratne, Henrik Böstrom

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Logic based methods for learning from structured data is limited w.r.t. handling large search spaces, preventing large-sized substructures from being considered by the resulting classifiers. A novel approach to learning from structured data is introduced that employs a structure transformation method, called finger printing, for addressing these limitations. The method, which generates features corresponding to arbitrarily complex substructures, is implemented in a system, called DIFFER. The method is demonstrated to perform comparably to an existing state-of-art method on some benchmark data sets without requiring restrictions on the search space. Furthermore, learning from the union of features generated by finger printing and the previous method outperforms learning from each individual set of features on all benchmark data sets, demonstrating the benefit of developing complementary, rather than competing, methods for structure classification.

Keywords: Machine learning, Structure classification, Propositionalization.

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Authors: Natarajan Vijayarangan, Prasanna S. Bidare

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Cryptography, Image watermarking and E-banking are filled with apparent oxymora and paradoxes. Random sequences are used as keys to encrypt information to be used as watermark during embedding the watermark and also to extract the watermark during detection. Also, the keys are very much utilized for 24x7x365 banking operations. Therefore a deterministic random sequence is very much useful for online applications. In order to obtain the same random sequence, we need to supply the same seed to the generator. Many researchers have used Deterministic Random Number Generators (DRNGs) for cryptographic applications and Pseudo Noise Random sequences (PNs) for watermarking. Even though, there are some weaknesses in PN due to attacks, the research community used it mostly in digital watermarking. On the other hand, DRNGs have not been widely used in online watermarking due to its computational complexity and non-robustness. Therefore, we have invented a new design of generating DRNG using Pi-series to make it useful for online Cryptographic, Digital watermarking and Banking applications.

Keywords: E-tokens, LFSR, non-linear, Pi series, pseudo random number.

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Authors: Walid S. Alfuhaid, Saud A. Alghamdi, John M. Watkins, M. Edwin Sawan

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Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.

Keywords: Decentralized, optimal control, output, singular perturb.

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Authors: Nebojsa B. Raicevic, Teodoros S. Prokic, Vladan Golubovic

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Recently, bianisotropic media again received increasing importance in electromagnetic theory because of advances in material science which enable the manufacturing of complex bianisotropic materials. By using Maxwell's equations and corresponding boundary conditions, the electromagnetic field distribution in bianisotropic solenoid coils is determined and the influence of the bianisotropic behaviour of coil to the impedance and Q-factor is considered. Bianisotropic media are the largest class of linear media which is able to describe the macroscopic material properties of artificial dielectrics, artificial magnetics, artificial chiral materials, left-handed materials, metamaterials, and other composite materials. Several special cases of coils, filled with complex substance, have been analyzed. Results obtained by using the analytical approach are compared with values calculated by numerical methods, especially by our new hybrid EEM/BEM method and FEM.

Keywords: Bianisotropic media, impedance and Q-factor, Maxwell`s equations, hybrid EEM/BEM method.

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent transportation systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning.

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Authors: Abdurahman H. Nour, Rosli M. Yunus, Azhary. H. Nour

Abstract:

The mechanism of microwave heating is essentially that of dielectric heating. After exposing the emulsion to the microwave Electromagnetic (EM) field, molecular rotation and ionic conduction due to the penetration of (EM) into the emulsion are responsible for the internal heating. To determine the capability of microwave technology in demulsification of crude oil emulsions, microwave demulsification method was applied in a 50-50 % and 20- 80 % water-in-oil emulsions with microwave exposure time varied from 20-180 sec. Transient temperature profiles of water-in-oil emulsions inside a cylindrical container were measured. The temperature rise at a given location was almost horizontal (linear). The average rates of temperature increase of 50-50 % and 20-80 % water-in-oil emulsions are 0.351 and 0.437 oC/sec, respectively. The rate of temperature increase of emulsions decreased at higher temperature due to decreasing dielectric loss of water. These results indicate that microwave demulsification of water-in-oil emulsions does not require chemical additions. Microwave has the potential to be used as an alternative way in the demulsification process.

Keywords: Demulsification, temperature profile, emulsion.Microwave heating, dielectric, volume rate.

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Authors: Carlos Mendez Galindo, Toshiro Hayashikawa, Javier Gil Belda

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This paper investigates the effectiveness of the use of seismic isolation devices on the overall 3D seismic response of curved highway viaducts with an emphasis on expansion joints. Furthermore, an evaluation of the effectiveness of the use of cable restrainers is presented. For this purpose, the bridge seismic performance has been evaluated on four different radii of curvature, considering two cases: restrained and unrestrained curved viaducts. Depending on the radius of curvature, three-dimensional non-linear dynamic analysis shows the vulnerability of curved viaducts to pounding and deck unseating damage. In this study, the efficiency of using LRB supports combined with cable restrainers on curved viaducts is demonstrated, not only by reducing in all cases the possible damage, but also by providing a similar behavior in the viaducts despite of curvature radius.

Keywords: Nonlinear dynamic response, seismic design, seismic isolation, unseating prevention system.

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Authors: Niloufar Ghoreishi, Ali Nekouzadeh

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The stability of the flight during maneuvering and in response to probable perturbations is one of the most essential features of an aircraft that should be analyzed and designed for. In this study, we derived the non-linear governing equations of aircraft dynamics during the climb/descend phase and simulated a model aircraft. The corresponding force and moment dimensionless coefficients of the model and their variations with elevator angle and other relevant aerodynamic parameters were measured experimentally. The short-period mode and phugoid mode response were simulated by solving the governing equations numerically and then compared with the desired stability parameters for the particular level, category, and class of the aircraft model. To meet the target stability, a controller was designed and used. This resulted in significant improvement in the stability parameters of the flight.

Keywords: Flight stability, phugoid mode, short period mode, climb phase, damping coefficient.

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: Microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks.

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Authors: A. Almasi

Abstract:

Reciprocating compressors are flexible to handle wide capacity and condition swings, offer a very efficient method of compressing almost any gas mixture in wide range of pressure, can generate high head independent of density, and have numerous applications and wide power ratings. These make them vital component in various units of industrial plants. In this paper optimum reciprocating compressor configuration regarding interstage pressures, low suction pressure, non-lubricated cylinder, speed of machine, capacity control system, compressor valve, lubrication system, piston rod coating, cylinder liner material, barring device, pressure drops, rod load, pin reversal, discharge temperature, cylinder coolant system, performance, flow, coupling, special tools, condition monitoring (including vibration, thermal and rod drop monitoring), commercial points, delivery and acoustic conditions are presented.

Keywords: Design, optimum, reciprocating compressor.

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Authors: Th. Arti Devi, Parthasarthi Choudhury

Abstract:

Extreme rainfall frequency analysis for Meteorological Sub-Division 4 of India was analyzed using L-moments approach. Serial Correlation and Mann Kendall tests were conducted for checking serially independent and stationarity of the observations. The discordancy measure for the sites was conducted to detect the discordant sites. The regional homogeneity was tested by comparing with 500 generated homogeneous regions using a 4 parameter Kappa distribution. The best fit distribution was selected based on Z^DIST statistics and L-moments ratio diagram from the five extreme value distributions GPD, GLO, GEV, P3 and LP3. The LN3 distribution was selected and regional rainfall frequency relationship was established using index-rainfall procedure. A regional mean rainfall relationship was developed using multiple linear regression with latitude and longitude of the sites as variables.

Keywords: L-moments, ZDIST statistics, Serial correlation, Mann Kendall test.

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Authors: Sahil Sharma, Mukesh Gupta, Raj Kumar, N. S Bindra

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This paper presents an experimental investigation on the optimization and the effect of the cutting parameters on Material Removal Rate (MRR) in Plasma Arc Cutting (PAC) of EN-45A Material using Taguchi L ₁₆ orthogonal array method. Four process variables viz. cutting speed, current, stand-off-distance and plasma gas pressure have been considered for this experimental work. Analysis of variance (ANOVA) has been performed to get the percentage contribution of each process parameter for the response variable i.e. MRR. Based on ANOVA, it has been observed that the cutting speed, current and the plasma gas pressure are the major influencing factors that affect the response variable. Confirmation test based on optimal setting shows the better agreement with the predicted values.

Keywords: Analysis of variance, Material removal rate, plasma arc cutting, Taguchi method.

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Authors: Ion Smeureanu, Adriana Reveiu, Marian Dardala, Titus Felix Furtuna, Roman Kanala

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This paper proposes a linear model for optimizing domestic energy consumption in Romania. The particularity of the model is that it is putting in competition both tangible technologies and thermal insulation projects with different financing modes. The model is optimizing the energy system by minimizing the global discounted cost in household sector, by integrating residential lighting, space heating, hot water, combined space heating – hot water, as well as space cooling, in a monolithic model. Another demand sector included is the passenger transport. This paper focuses on space heating part, analyzing technical and economic issues related to investment decisions to envelope and insulate buildings, in order to minimize energy consumption.

Keywords: Consumer behavior, energy modelling, Open Source Energy Modeling System (OSeMOSYS), MARKAL/TIMES Romanian energy model.

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Authors: Priyanka Guin, Dibyendu Chatterjee, Arijit Roy

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Developing electronic system for detecting low energy impacts using open source hardware such as Arduino is challenging. A highly efficient loadcell is designed and fabricated. A commercial polyvinylidene fluoride (PVDF) piezoelectric film is used as primary sensor for sensing small impacts. Without modifying hardware, the Arduino board is configured by programming to capture the signal from the film sensor with a resolution better than 1.1 mV. By our system, impact energy as low as 1.8 µJ (corresponds to impact force of 39.9 mN) is reliably and monitored. In the linear zone, sensitivity of the system found to be as high as 20.7 kV/J or 3.3 V/N with a measurement frequency of 500 Hz. The various characteristics such as linearity, hysteresis, repeatability and spectrum analysis are discussed. After calibration, measurements of unknown impact energy and impact force are investigated and results are found to agree well.

Keywords: Arduino, impact energy, impact force, measurement system, PVDF film sensor.

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Authors: Hussain A. Alkharusi, Said S. Aldhafri, Hilal Z. Alnabhani, Muna Alkalbani

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Analyzing classroom assessments is one of the responsibilities of the teacher. It aims improving teacher’s instruction and assessment as well as student learning. The present study investigated factors that might explain variation in teachers’ practices regarding analysis of classroom assessments. The factors considered in the investigation included gender, in-service assessment training, teaching load, teaching experience, knowledge in assessment, attitude towards quantitative aspects of assessment, and self-perceived competence in analyzing assessments. Participants were 246 in-service teachers in Oman. Results of a stepwise multiple linear regression analysis revealed that self-perceived competence was the only significant factor explaining the variance in teachers’ analysis of assessments. Implications for research and practice are discussed.

 

Keywords: Analysis of assessment, Classroom assessment, In-service teachers, Self-competence.

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Authors: Abdul Rahim Yacob, Mohamad Raizul Zinalibdin

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A simple method for the simultaneous determination of hippuric acid and benzoic acid in urine using reversed-phase high performance liquid chromatography was described. Chromatography was performed on a Nova-Pak C18 (3.9 x 150 mm) column with a mobile phase of mixed solution methanol: water: acetic acid (20:80:0.2) and UV detection at 254 nm. The calibration curve was linear within concentration range at 0.125 to 6.0 mg/ml of hippuric acid and benzoic acid. The recovery, accuracy and coefficient variance of hippuric acid were 104.54%, 0.2% and 0.2% respectively and for benzoic acid were 98.48%, 1.25% and 0.60% respectively. The detection limit of this method was 0.01ng/l for hippuric acid and 0.06ng/l for benzoic acid. This method has been applied to the analysis of urine samples from the suspected of toluene abuser or glue sniffer among secondary school students at Johor Bahru.

Keywords: Glue sniffer, High Performance LiquidChromatography, Hippuric Acid, Toluene, Urine.

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Authors: Malika Yaici, Kamel Hariche, Tim Clarke

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The relationship between eigenstructure (eigenvalues and eigenvectors) and latent structure (latent roots and latent vectors) is established. In control theory eigenstructure is associated with the state space description of a dynamic multi-variable system and a latent structure is associated with its matrix fraction description. Beginning with block controller and block observer state space forms and moving on to any general state space form, we develop the identities that relate eigenvectors and latent vectors in either direction. Numerical examples illustrate this result. A brief discussion of the potential of these identities in linear control system design follows. Additionally, we present a consequent result: a quick and easy method to solve the polynomial eigenvalue problem for regular matrix polynomials.

Keywords: Eigenvalues/Eigenvectors, Latent values/vectors, Matrix fraction description, State space description.

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Authors: Naoya Ozaki, Takuya Watanabe, Ryosuke Matsumoto, Noriko Fukasawa

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In the metropolitan areas in Japan, in many stations, shopping areas are set up, and escalators and elevators are installed to make the stations be barrier-free. Further, many areas around the stations are being redeveloped. Railway business operators want to know how much effect these circumstances have on attractiveness of the station or number of passengers using the station. So, we performed a questionnaire survey of the station users in the metropolitan areas for finding factors to affect the attractiveness of stations. Then, based on the analysis of the survey, we developed a method to quantitatively evaluate attractiveness of the stations. We also developed an estimation method for number of passengers based on combination of attractiveness of the station quantitatively evaluated and the residential and labor population around the station. Then, we derived precise linear regression models estimating the attractiveness of the station and number of passengers of the station.

Keywords: Attractiveness of the station, estimation method, number of passengers of the station, redevelopment around the station, renovation of the station.

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Authors: M. Siosemarde, F. Kave, E. Pazira, H. Sedghi, S. J. Ghaderi

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Researchers have long had trouble in measurement of Exchangeable Sodium Ratio (ESR) at salt-affected soils. this parameter are often determined using laborious and time consuming laboratory tests, but it may be more appropriate and economical to develop a method which uses a more simple soil salinity index. The aim of this study was to determine the relationship between exchangeable sodium ratio (ESR) and sodium adsorption ratio (SAR) in some salt-affected soils of Khuzestan plain. To this purpose, two experimental areas (S1, S2) of Khuzestan province-IRAN were selected and four treatments with three replications by series of double rings were applied. The treatments were included 25cm, 50cm, 75cm and 100cm water application. The statistical results of the study indicated that in order to predict soil ESR based on soil SAR the linear regression model ESR=0.2048+0.0066 SAR (R2=0.53) & ESR=0.0564+0.0171 SAR (R2=0.76) can be recommended in Pilot S1 and S2 respectively.

Keywords: exchangeable sodium ratio, Khuzestan plain, saltaffectedsoils and sodium adsorption ratio.

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Authors: Ömer Aktaş, Olga A. Suvorova, Oleg Tretyakov

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The boundary value problem on non-canonical and arbitrary shaped contour is solved with a numerically effective method called Analytical Regularization Method (ARM) to calculate propagation parameters. As a result of regularization, the equation of first kind is reduced to the infinite system of the linear algebraic equations of the second kind in the space of L₂. This equation can be solved numerically for desired accuracy by using truncation method. The parameters as cut-off wavenumber and cut-off frequency are used in waveguide evolutionary equations of electromagnetic theory in time-domain to illustrate the real-valued TM fields with lossy and lossless media.

Keywords: Arbitrary cross section waveguide, analytical regularization method, evolutionary equations of electromagnetic theory of time-domain, TM field.

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Authors: Murat Koklu, Yavuz Unal

Abstract:

Data mining can be called as a technique to extract information from data. It is the process of obtaining hidden information and then turning it into qualified knowledge by statistical and artificial intelligence technique. One of its application areas is medical area to form decision support systems for diagnosis just by inventing meaningful information from given medical data. In this study a decision support system for diagnosis of illness that make use of data mining and three different artificial intelligence classifier algorithms namely Multilayer Perceptron, Naive Bayes Classifier and J.48. Pima Indian dataset of UCI Machine Learning Repository was used. This dataset includes urinary and blood test results of 768 patients. These test results consist of 8 different feature vectors. Obtained classifying results were compared with the previous studies. The suggestions for future studies were presented.

Keywords: Artificial Intelligence, Classifiers, Data Mining, Diabetic Patients.

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Authors: W. Srisang, K. Jaroensutasinee, M. Jaroensutasinee

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This study aimed at developing visualization tools for integrating CloudSat images and Water Vapor Satellite images. KML was used for integrating data from CloudSat Satellite and GMS-6 Water Vapor Satellite. CloudSat 2D images were transformed into 3D polygons in order to achieve 3D images. Before overlaying the images on Google Earth, GMS-6 water vapor satellite images had to be rescaled into linear images. Web service was developed using webMathematica. Shoreline from GMS-6 images was compared with shoreline from LandSat images on Google Earth for evaluation. The results showed that shoreline from GMS-6 images was highly matched with the shoreline in LandSat images from Google Earth. For CloudSat images, the visualizations were compared with GMS-6 images on Google Earth. The results showed that CloudSat and GMS-6 images were highly correlated.

Keywords: CloudSat, Water vapor, Satellite images, GoogleEarth™.

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