Search results for: hyperbolic function models.

Authors: Adarsh Venkataraman Ganesan, Sundaram Swaminathan, Rama Jayaraj

Abstract:

Human middle-ear is the key component of the auditory system. Its function is to transfer the sound waves through the ear canal to provide sufficient stimulus to the fluids of the inner ear. Degradation of the ossicles that transmit these sound waves from the eardrum to the inner ear leads to hearing loss. This problem can be overcome by replacing one or more of these ossicles by middleear prosthesis. Designing such prosthesis requires a comprehensive knowledge of the biomechanics of the middle-ear. There are many finite element modeling approaches developed to understand the biomechanics of the middle ear. The available models in the literature, involve high computation time. In this paper, we propose a simplified model which provides a reasonably accurate result with much less computational time. Simulation results indicate a maximum sound pressure gain of 10 dB at 5500 Hz.

Keywords: Ear, Ossicles, COMSOL, Stapes.

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Authors: Dení Stincer Gómez, Zuraya Monroy Nasr

Abstract:

Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional mechanisms. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the so-called content-bearing function: it argues that emotions provide the material reasoning that is subsequently transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. This paper argues that science education must start from the presence of certain emotions in the learner if we want to form citizens with a scientific or cultural future.

Keywords: Epistemic emotions, science education, formation of citizens and scientists, epistemic functions of emotions.

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Authors: S. B. Mansuri

Abstract:

In this paper, at first we explain about negative hypergeometric distribution and its properties. Then we use the w-function and the Stein identity to give a result on the poisson approximation to the negative hypergeometric distribution in terms of the total variation distance between the negative hypergeometric and poisson distributions and its upper bound.

Keywords: Negative hypergeometric distribution, Poisson distribution, Poisson approximation, Stein-Chen identity, w-function.

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Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: Cross-validation, decision tree, lagged variables, short-term forecasting.

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Authors: L. Grinis

Abstract:

Turbulent flow in complex geometries receives considerable attention due to its importance in many engineering applications. It has been the subject of interest for many researchers. Some of these interests include the design of storm water channels. The design of these channels requires testing through physical models. The main practical limitation of physical models is the so called “scale effect”, that is, the fact that in many cases only primary physical mechanisms can be correctly represented, while secondary mechanisms are often distorted. These observations form the basis of our study, which centered on problems associated with the design of storm water channels near the Dead Sea, in Israel. To help reach a final design decision we used different physical models. Our research showed good coincidence with the results of laboratory tests and theoretical calculations, and allowed us to study different effects of fluid flow in an open channel. We determined that problems of this nature cannot be solved only by means of theoretical calculation and computer simulation. This study demonstrates the use of physical models to help resolve very complicated problems of fluid flow through baffles and similar structures. The study applies these models and observations to different construction and multiphase water flows, among them, those that include sand and stone particles, a significant attempt to bring to the testing laboratory a closer association with reality.

Keywords: Baffles, open channel, physical modeling.

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Authors: Bi-Huei Tsai

Abstract:

Previous studies on financial distress prediction choose the conventional failing and non-failing dichotomy; however, the distressed extent differs substantially among different financial distress events. To solve the problem, “non-distressed”, “slightlydistressed” and “reorganization and bankruptcy” are used in our article to approximate the continuum of corporate financial health. This paper explains different financial distress events using the two-stage method. First, this investigation adopts firm-specific financial ratios, corporate governance and market factors to measure the probability of various financial distress events based on multinomial logit models. Specifically, the bootstrapping simulation is performed to examine the difference of estimated misclassifying cost (EMC). Second, this work further applies macroeconomic factors to establish the credit cycle index and determines the distressed cut-off indicator of the two-stage models using such index. Two different models, one-stage and two-stage prediction models are developed to forecast financial distress, and the results acquired from different models are compared with each other, and with the collected data. The findings show that the one-stage model has the lower misclassification error rate than the two-stage model. The one-stage model is more accurate than the two-stage model.

Keywords: Multinomial logit model, corporate governance, company failure, reorganization, bankruptcy.

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Authors: Kholod M. Abualnaja

Abstract:

This paper consider the solution of the matrix differential models using quadratic, cubic, quartic, and quintic splines. Also using the Taylor’s and Picard’s matrix methods, one illustrative example is included.

Keywords: Matrix Splines, Cubic Splines, Quartic Splines.

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Authors: M. Byzedi, B. Saghafian

Abstract:

Droughts are complex, natural hazards that, to a varying degree, affect some parts of the world every year. The range of drought impacts is related to drought occurring in different stages of the hydrological cycle and usually different types of droughts, such as meteorological, agricultural, hydrological, and socioeconomical are distinguished. Streamflow drought was analyzed by the method of truncation level (at 70% level) on daily discharges measured in 54 hydrometric stations in southwestern Iran. Frequency analysis was carried out for annual maximum series (AMS) of drought deficit volume and duration series. Some factors including physiographic, climatic, geologic, and vegetation cover were studied as influential factors in the regional analysis. According to the results of factor analysis, six most effective factors were identified as area, rainfall from December to February, the percent of area with Normalized Difference Vegetation Index (NDVI) <0.1, the percent of convex area, drainage density and the minimum of watershed elevation that explained 90.9% of variance. The homogenous regions were determined by cluster analysis and discriminate function analysis. Suitable multivariate regression models were evaluated for streamflow drought deficit volume with 2 years return period. The significance level of regression models was 0.01. The results showed that the watershed area is the most effective factor with high correlation with deficit volume. Also, drought duration was not a suitable drought index for regional analysis.

Keywords: Iran, Streamflow drought, truncation level method, regional analysis.

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Authors: Mária Stachová, Lukáš Sobíšek

Abstract:

Data mining incorporates a group of statistical methods used to analyze a set of information, or a data set. It operates with models and algorithms, which are powerful tools with the great potential. They can help people to understand the patterns in certain chunk of information so it is obvious that the data mining tools have a wide area of applications. For example in the theoretical chemistry data mining tools can be used to predict moleculeproperties or improve computer-assisted drug design. Classification analysis is one of the major data mining methodologies. The aim of thecontribution is to create a classification model, which would be able to deal with a huge data set with high accuracy. For this purpose logistic regression, Bayesian logistic regression and random forest models were built using R software. TheBayesian logistic regression in Latent GOLD software was created as well. These classification methods belong to supervised learning methods. It was necessary to reduce data matrix dimension before construct models and thus the factor analysis (FA) was used. Those models were applied to predict the biological activity of molecules, potential new drug candidates.

Keywords: data mining, classification, drug design, QSAR

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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: S. Thirumurugan, D. R. Prince Williams

Abstract:

Software Reliability is one of the key factors in the software development process. Software Reliability is estimated using reliability models based on Non Homogenous Poisson Process. In most of the literature the Software Reliability is predicted only in testing phase. So it leads to wrong decision-making concept. In this paper, two Software Reliability concepts, testing and operational phase are studied in detail. Using S-Shaped Software Reliability Growth Model (SRGM) and Exponential SRGM, the testing and operational reliability values are obtained. Finally two reliability values are compared and optimal release time is investigated.

Keywords: Error Detection Rate, Estimation of Parameters, Instantaneous Failure Rate, Mean Value Function, Non Homogenous Poisson Process (NHPP), Software Reliability.

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Authors: Wang Xing-hua, Zhong Shun-an, Zhang Zhuo

Abstract:

A kind of behavior model for discrete sampling and hold amplifier with charge transmission is analyzed. The transfer function and behavior features are based on the main AC responses of operation amplifier. The result used in pipelined and sigma-delta ADC shows the exact of model of sampling and hold amplifier, and the non-ideal factors are taken into account.

Keywords: SHA, response, behavior, transfer function.

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Authors: Boonorm Chomtee, John J. Borkowski

Abstract:

The objective of the research is to study and compare response surface designs: Central composite designs (CCD), Box- Behnken designs (BBD), Small composite designs (SCD), Hybrid designs, and Uniform shell designs (USD) over sets of reduced models when the design is in a spherical region for 3 and 4 design variables. The two optimality criteria ( D and G ) are considered which larger values imply a better design. The comparison of design optimality criteria of the response surface designs across the full second order model and sets of reduced models for 3 and 4 factors based on the two criteria are presented.

Keywords: design optimality criteria, reduced models, response surface design, spherical design region

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Authors: Somayeh Komeylian

Abstract:

The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, adaptive antenna array, Deep Neural Network, LS-SVM optimization model, radial basis function, MSE.

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Authors: Nima Hatami

Abstract:

In this paper, we use Radial Basis Function Networks (RBFN) for solving the problem of environmental interference cancellation of speech signal. We show that the Second Order Thin- Plate Spline (SOTPS) kernel cancels the interferences effectively. For make comparison, we test our experiments on two conventional most used RBFN kernels: the Gaussian and First order TPS (FOTPS) basis functions. The speech signals used here were taken from the OGI Multi-Language Telephone Speech Corpus database and were corrupted with six type of environmental noise from NOISEX-92 database. Experimental results show that the SOTPS kernel can considerably outperform the Gaussian and FOTPS functions on speech interference cancellation problem.

Keywords: Environmental interference, interference cancellation of speech, Radial Basis Function networks, Gaussian and TPS kernels.

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Authors: Abdellatif Kasbi, Abderrafii Rahali

Abstract:

In an electric power grid connected wind generation system, dynamic control strategy is essential to use the wind energy efficiently as well as for an energy optimization. The present study has focused on decoupled power regulation of doubly fed induction generator, operating in wind turbine, in accordance with the vector control approach by applying fractional order proportional integral (FOPI) controller. The FOPI controller is designed based on a simple method; up such that the response of closed loop process is similar to the response of a specified fractional model whose transfer function is Bode’s ideal function. In this tuning operation, the parameters of the proposed fractional controller are established analytically using the impulse closed-loop response of the controlled process. To show the superior action of the developed FOPI controller in comparison with standard PI controller in different function conditions, the study is validated through simulation using the software MATLAB/Simulink.

Keywords: Wind generation system, DFIG, vector control approach, fractional order PI controller, Bode’s ideal transfer function, impulse response.

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Authors: S. Boria

Abstract:

In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: Composite material, crashworthiness, finite element analysis, optimization.

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Authors: Vijaya K. Srivastava, Davide Spinello

Abstract:

This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3ⁿ enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3ⁿ integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.

Keywords: Constrained integer problems, enumerative search algorithm, Heuristic algorithm, tunneling algorithm.

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Authors: Yoichi Ishikawa, Yuichi Masukake, Yoshihisa Ishida

Abstract:

This paper presents a novel control method based on radial basis function networks (RBFNs) for chaotic dynamical systems. The proposed method first identifies the nonlinear part of the chaotic system off-line and then constructs a model-following controller using only the estimated system parameters. Simulation results show the effectiveness of the proposed control scheme.

Keywords: Chaos, nonlinear plant, radial basis function network.

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Authors: Belkacem Chikhaoui, Helene Pigot

Abstract:

Cognitive models allow predicting some aspects of utility and usability of human machine interfaces (HMI), and simulating the interaction with these interfaces. The action of predicting is based on a task analysis, which investigates what a user is required to do in terms of actions and cognitive processes to achieve a task. Task analysis facilitates the understanding of the system-s functionalities. Cognitive models are part of the analytical approaches, that do not associate the users during the development process of the interface. This article presents a study about the evaluation of a human machine interaction with a contextual assistant-s interface using ACTR and GOMS cognitive models. The present work shows how these techniques may be applied in the evaluation of HMI, design and research by emphasizing firstly the task analysis and secondly the time execution of the task. In order to validate and support our results, an experimental study of user performance is conducted at the DOMUS laboratory, during the interaction with the contextual assistant-s interface. The results of our models show that the GOMS and ACT-R models give good and excellent predictions respectively of users performance at the task level, as well as the object level. Therefore, the simulated results are very close to the results obtained in the experimental study.

Keywords: HMI, interface evaluation, Analytical evaluation, cognitivemodeling, user modeling, user performance.

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Authors: Yong-Taeg Oh, Won Song, Seok-Eui Choi, Bo-Ra Koo, Dong-Chan Shin

Abstract:

ZnO+Ga2O3 functionally graded thin films (FGTFs) were examined for their potential use as Solar cell and organic light emitting diodes (OLEDs). FGTF transparent conducting oxides (TCO) were fabricated by combinatorial RF magnetron sputtering. The composition gradient was controlled up to 10% by changing the plasma power of the two sputter guns. A Ga2O3+ZnO graded region was placed on the top layer of ZnO. The FGTFs showed up to 80% transmittance. Their surface resistances were reduced to < 10% by increasing the Ga2O3: pure ZnO ratio in the TCO. The FGTFs- work functions could be controlled within a range of 0.18 eV. The controlled work function is a very promising technology because it reduces the contact resistance between the anode and Hall transport layers of OLED and solar cell devices.

Keywords: Work Function, TCO, Functionally Graded Thin Films, Resistance, Transmittance.

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Authors: Yuri Boiko, Iluju Kiringa, Tet Yeap

Abstract:

Current drainage attack suggested previously is further studied in regular settings of closed-loop controlled Brushless DC (BLDC) motor with Kalman filter in the feedback loop. Modeling and simulation experiments are conducted in a MATLAB environment, implementing the closed-loop control model of BLDC motor operation in position sensorless mode under Kalman filter drive. The current increase in the motor windings is caused by the controller (p-controller in our case) affected by false data injection of substitution of the angular velocity estimates with distorted values. Operation of multiplication to distortion coefficient, values of which are taken from the distortion function synchronized in its periodicity with the rotor’s position change. A saw function with a triangular tooth shape is studied herewith for the purpose of carrying out the bias injection with current drainage consequences. The specific focus here is on how the asymmetry of the tooth in the saw function affects the flow of current drainage. The purpose is two-fold: (i) to produce and collect the signature of an asymmetric saw in the attack for further pattern recognition process, and (ii) to determine conditions of improving stealthiness of such attack via regulating asymmetry in saw function used. It is found that modification of the symmetry in the saw tooth affects the periodicity of current drainage modulation. Specifically, the modulation frequency of the drained current for a fully asymmetric tooth shape coincides with the saw function modulation frequency itself. Increasing the symmetry parameter for the triangle tooth shape leads to an increase in the modulation frequency for the drained current. Moreover, such frequency reaches the switching frequency of the motor windings for fully symmetric triangular shapes, thus becoming undetectable and improving the stealthiness of the attack. Therefore, the collected signatures of the attack can serve for attack parameter identification via the pattern recognition route.

Keywords: Bias injection attack, Kalman filter, BLDC motor, control system, closed loop, P-controller, PID-controller, current drainage, saw-function, asymmetry.

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Authors: Min Kyung An

Abstract:

In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: Data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional.

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Authors: Rongtao Ding, Xinhao Ji, Linting Zhu

Abstract:

In recent years, the relevance feedback technology is regarded in content-based image retrieval. This paper suggests a neural networks feedback algorithm based on the radial basis function, coming to extract the semantic character of image. The results of experiment indicated that the performance of this relevance feedback is better than the feedback algorithm based on Single-RBF.

Keywords: Image retrieval, relevance feedback, radial basis function.

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Authors: Mahasen M. Abdel-Mageed, H. S. Zaghloul

Abstract:

Annihilations, phase shifts, scattering lengths and elastic cross sections of low energy positrons scattering from magnesium atoms were studied using the least-squares variational method (LSVM). The possibility of positron binding to the magnesium atoms is investigated. A trial wave function is suggested to represent e+-Mg elastic scattering and scattering parameters were derived to estimate the binding energy and annihilation rates. The trial function is taken to depend on several adjustable parameters, and is improved iteratively by increasing the number of terms. The present results have the same behavior as reported semi-empirical, theoretical and experimental results. Especially, the estimated positive scattering length supports the possibility of positronmagnesium bound state system that was confirmed in previous experimental and theoretical work.

Keywords: Bound wave function, Positron Annihilation, scattering phase shift, scattering length.

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Authors: N. Sopipan

Abstract:

In this paper, we study the rainfall using a time series for weather stations in Nakhon Ratchasima province in Thailand by various statistical methods to enable us to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. The ARIMA and Holt-Winter models were built on the basis of exponential smoothing. All the models proved to be adequate. Therefore it is possible to give information that can help decision makers establish strategies for the proper planning of agriculture, drainage systems and other water resource applications in Nakhon Ratchasima province. We obtained the best performance from forecasting with the ARIMA Model(1,0,1)(1,0,1)12.

Keywords: ARIMA Models, Exponential Smoothing, Holt- Winter model.

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

Abstract:

The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: Data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse.

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Authors: Kaveh Mohammad Cyrus, Shadi Sanagoo

Abstract:

MABENA model is a complementary model in comparison with traditional models such as HCMS, CMS and etc. New factors, which have effects on preparation of strategic plans and their sequential order in MABENA model is the platform of presented road map in this paper.Study review shows, factors such as emerging new critical success factors for strategic planning, improvement of international strategic models, increasing the maturity of companies and emerging new needs leading to design a new model which can be responsible for new critical factors and solve the limitations of previous strategic management models. Preparation of strategic planning need more factors than introduced in traditional models. The needed factors includes determining future Critical Success Factors and competencies, defining key processes, determining the maturity of the processes, considering all aspects of the external environment etc. Description of aforementioned requirements, the outcomes and their order is developing and presenting the MABENA model-s road map in this paper. This study presents a road map for strategic planning of the Iranian organizations.

Keywords: Competitive Advantage, Process Maturity, StrategicPlanning, Strategic potential

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Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

Abstract:

Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: Airborne laser scanning, digital terrain models, filtering, forested areas.

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Authors: M. Mordjaoui, B. Boudjema, M. Chabane, R. Daira

Abstract:

In determining the electromagnetic properties of magnetic materials, hysteresis modeling is of high importance. Many models are available to investigate those characteristics but they tend to be complex and difficult to implement. In this paper a new qualitative hysteresis model for ferromagnetic core is presented, based on the function approximation capabilities of adaptive neuro fuzzy inference system (ANFIS). The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach can restored the hysteresis curve with a little RMS error. The model accuracy is good and can be easily adapted to the requirements of the application by extending or reducing the network training set and thus the required amount of measurement data.

Keywords: ANFIS modeling technique, magnetic hysteresis, Jiles-Atherton model, ferromagnetic core.

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