Search results for: Locally Linear Neuro-Fuzzy model.

Authors: Sagaren Pillay

Abstract:

In this paper bi-annual time series data on unemployment rates (from the Labour Force Survey) are expanded to quarterly rates and linked to quarterly unemployment rates (from the Quarterly Labour Force Survey). The resultant linked series and the consumer price index (CPI) series are examined using Johansen’s cointegration approach and vector error correction modeling. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant co-integrating relationship is found to exist between the time series of unemployment rates and the CPI. Given this significant relationship, the study models this relationship using Vector Error Correction Models (VECM), one with a restriction on the deterministic term and the other with no restriction.

A formal statistical confirmation of the existence of a unique linear and lagged relationship between inflation and unemployment for the period between September 2000 and June 2011 is presented. For the given period, the CPI was found to be an unbiased predictor of the unemployment rate. This relationship can be explored further for the development of appropriate forecasting models incorporating other study variables.

Keywords: Forecasting, lagged, linear, relationship.

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Authors: Fanqiang Kong, Chending Bian

Abstract:

In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: Hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation.

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Authors: Yongxin Yuan, Jiashang Jiang

Abstract:

A new numerical method for simultaneously updating mass and stiffness matrices based on incomplete modal measured data is presented. By using the Kronecker product, all the variables that are to be modified can be found out and then can be updated directly. The optimal approximation mass matrix and stiffness matrix which satisfy the required eigenvalue equation and orthogonality condition are found under the Frobenius norm sense. The physical configuration of the analytical model is preserved and the updated model will exactly reproduce the modal measured data. The numerical example seems to indicate that the method is quite accurate and efficient.

Keywords: Finite element model, model updating, modal data, optimal approximation.

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Authors: H. Zemmouri, H. Lounic, N. Mameri

Abstract:

The present study aims to investigate the performance of Moringa oleifera seed extract as natural coagulant in clarification of secondary wastewater treatment plant (MWWTP) located in East of Algiers, Algeria. Coagulation flocculation performance of Moringa oleifera was evaluated through supernatant residual turbidity after jar test trials. Various influence parameters namely Moringa oleifera dosage and pH have been considered. Tests on Reghaia wastewater, having 129 NTU of initial turbidity, showed a removal of 69.45% of residual turbidity with only 1.5 mg/l of Moringa oleifera. This sufficient removal capability encourages the use of this bioflocculant for treatment of turbid waters. Indeed, Moringa oleifera which is a natural resource available locally (South of Algeria) coupled to the non-toxicity, biocompatibility and biodegradability, may be a very interesting alternative to the conventional coagulants used so far.

Keywords: Coagulation flocculation, colloids, Moringa oleifera, secondary wastewater.

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Authors: S.Shokri, S.Zahedi, M.Ahmadi Marvast, B. Baloochi, H.Ganji

Abstract:

In this research, a systematic investigation was carried out to determine the optimum conditions of HDS reactor. Moreover, a suitable model was developed for a rigorous RTO (real time optimization) loop of HDS (Hydro desulfurization) process. A systematic experimental series was designed based on CCD (Central Composite design) and carried out in the related pilot plant to tune the develop model. The designed variables in the experiments were Temperature, LHSV and pressure. However, the hydrogen over fresh feed ratio was remained constant. The ranges of these variables were respectively equal to 320-380ºC, 1- 21/hr and 50-55 bar. a power law kinetic model was also developed for our further research in the future .The rate order and activation energy , power of reactant concentration and frequency factor of this model was respectively equal to 1.4, 92.66 kJ/mol and k0=2.7*109 .

Keywords: Statistical model, Multiphase Reactors, Gas oil, Hydrodesulfurization, Optimization, Kinetics

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Authors: Amir Mohammad Fathollahi Fard, Mostafa Hajiaghaei-Keshteli, Mohammad Mahdi Paydar

Abstract:

With increasing life expectancy in developed countries, the role of home care services is highlighted by both academia and industrial contributors in Home Health Care Supply Chain (HHCSC) companies. The main decisions in such supply chain systems are the location of pharmacies, the allocation of patients to these pharmacies and also the routing and scheduling decisions of nurses to visit their patients. In this study, for the first time, an integrated model is proposed to consist of all preliminary and necessary decisions in these companies, namely, location-allocation-routing model. This model is a type of NP-hard one. Therefore, an Imperialist Competitive Algorithm (ICA) is utilized to solve the model, especially in large sizes. Results confirm the efficiency of the developed model for HHCSC companies as well as the performance of employed ICA.

Keywords: Home health care supply chain, location-allocation-routing problem, imperialist competitive algorithm, optimization.

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Authors: Hazem M. El-Bakry, Ahmed A. Saleh, Taghreed T. Asfour

Abstract:

Adaptive e-learning today gives the student a central role in his own learning process. It allows learners to try things out, participate in courses like never before, and get more out of learning than before. In this paper, an adaptive e-learning model for logic design, simplification of Boolean functions and related fields is presented. Such model presents suitable courses for each student in a dynamic and adaptive manner using existing database and workflow technologies. The main objective of this research work is to provide an adaptive e-learning model based learners' personality using explicit and implicit feedback. To recognize the learner-s, we develop dimensions to decide each individual learning style in order to accommodate different abilities of the users and to develop vital skills. Thus, the proposed model becomes more powerful, user friendly and easy to use and interpret. Finally, it suggests a learning strategy and appropriate electronic media that match the learner-s preference.

Keywords: Adaptive learning, Learning styles, Teaching strategies.

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Authors: Jia-Jang Wu

Abstract:

This paper presents the scaling laws that provide the criteria of geometry and dynamic similitude between the full-size rotor-shaft system and its scale model, and can be used to predict the torsional vibration characteristics of the full-size rotor-shaft system by manipulating the corresponding data of its scale model. The scaling factors, which play fundamental roles in predicting the geometry and dynamic relationships between the full-size rotor-shaft system and its scale model, for torsional free vibration problems between scale and full-size rotor-shaft systems are firstly obtained from the equation of motion of torsional free vibration. Then, the scaling factor of external force (i.e., torque) required for the torsional forced vibration problems is determined based on the Newton’s second law. Numerical results show that the torsional free and forced vibration characteristics of a full-size rotor-shaft system can be accurately predicted from those of its scale models by using the foregoing scaling factors. For this reason, it is believed that the presented approach will be significant for investigating the relevant phenomenon in the scale model tests.

Keywords: Torsional vibration, full-size model, scale model, scaling laws.

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Authors: Jung–Min Yang

Abstract:

Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the desired input/output behavior. A matrix expression is presented to address reachability of switched asynchronous sequential machines with output equivalence with respect to a model. The presented reachability condition for the controller design is validated in a simple example.

Keywords: Asynchronous sequential machines, corrective control, model matching, input/output control.

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Authors: K. Soldatova, Y. Galerkin

Abstract:

A loading factor performance is necessary for the modeling of centrifugal compressor gas dynamic performance curve. Measured loading factors are linear function of a flow coefficient at an impeller exit. The performance does not depend on the compressibility criterion. To simulate loading factor performances, the authors present two parameters: a loading factor at zero flow rate and an angle between an ordinate and performance line. The calculated loading factor performances of non-viscous are linear too and close to experimental performances. Loading factor performances of several dozens of impellers with different blade exit angles, blade thickness and number, ratio of blade exit/inlet height, and two different type of blade mean line configuration. There are some trends of influence, which are evident – comparatively small blade thickness influence, and influence of geometry parameters is more for impellers with bigger blade exit angles, etc. Approximating equations for both parameters are suggested. The next phase of work will be simulating of experimental performances with the suggested approximation equations as a base.

Keywords: Centrifugal compressor stage, centrifugal compressor, loading factor, gas dynamic performance curve.

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Authors: Mojtaba Mahdavi, Mohamad Mahdavi, Maryam Yazdani

Abstract:

A heuristic conceptual model for to develop the Reliability Centered Maintenance (RCM), especially in preventive strategy, has been explored during this paper. In most real cases which complicity of system obligates high degree of reliability, this model proposes a more appropriate reliability function between life time distribution based and another which is based on relevant Extreme Value (EV) distribution. A statistical and mathematical approach is used to estimate and verify these two distribution functions. Then best one is chosen just among them, whichever is more reliable. A numeric Industrial case study will be reviewed to represent the concepts of this paper, more clearly.

Keywords: Lifetime distribution, Reliability, Estimation, Extreme value, Improving model, Series, Parallel.

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Authors: N. H. Adenan, M. S. M. Noorani

Abstract:

River flow prediction is an essential tool to ensure proper management of water resources and the optimal distribution of water to consumers. This study presents an analysis and prediction by using nonlinear prediction method with monthly river flow data for Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The reconstruction of phase space involves the reconstruction of one-dimension (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. The revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) was employed to compare prediction performance for the nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show that the prediction results using the nonlinear prediction method are better than ARIMA and SVM. Therefore, the results of this study could be used to develop an efficient water management system to optimize the allocation of water resources.

Keywords: River flow, nonlinear prediction method, phase space, local linear approximation.

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

Abstract:

Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: Energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning.

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Authors: Spyridon Nikolaidis

Abstract:

A modeling approach for CMOS gates is presented based on the use of the equivalent inverter. A new model for the inverter has been developed using a simplified transistor current model which incorporates the nanoscale effects for the planar technology. Parametric expressions for the output voltage are provided as well as the values of the output and supply current to be compatible with the CCS technology. The model is parametric according the input signal slew, output load, transistor widths, supply voltage, temperature and process. The transistor widths of the equivalent inverter are determined by HSPICE simulations and parametric expressions are developed for that using a fitting procedure. Results for the NAND gate shows that the proposed approach offers sufficient accuracy with an average error in propagation delay about 5%.

Keywords: CMOS gate modeling, Inverter modeling, transistor current model, timing model.

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Authors: Mohammad Reza Oftadeh

Abstract:

The purpose of the article is to describe project objective structure (POS) concept that was developed on research activities and experiences about project management, Balanced Scorecard (BSC) and European Foundation Quality Management Excellence Model (EFQM Excellence Model). Furthermore, this paper tries to define a balanced, systematic, and integrated measurement approach to meet project objectives and project strategic goals based on a process-oriented model. In this paper, POS is suggested in order to measure project performance in the project life cycle. After using the POS model, the project manager can ensure in order to achieve the project objectives on the project charter. This concept can help project managers to implement integrated and balanced monitoring and control project work.

Keywords: Project objectives, project performance management, PMBOK, key performance indicators, integration management.

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Authors: Dariusz Dymek, Leszek Kotulski

Abstract:

Modeling of the distributed systems allows us to represent the whole its functionality. The working system instance rarely fulfils the whole functionality represented by model; usually some parts of this functionality should be accessible periodically. The reporting system based on the Data Warehouse concept seams to be an intuitive example of the system that some of its functionality is required only from time to time. Analyzing an enterprise risk associated with the periodical change of the system functionality, we should consider not only the inaccessibility of the components (object) but also their functions (methods), and the impact of such a situation on the system functionality from the business point of view. In the paper we suggest that the risk attributes should be estimated from risk attributes specified at the requirements level (Use Case in the UML model) on the base of the information about the structure of the model (presented at other levels of the UML model). We argue that it is desirable to consider the influence of periodical changes in requirements on the enterprise risk estimation. Finally, the proposition of such a solution basing on the UML system model is presented.

Keywords: Risk assessing, software maintenance, UML, graph grammars.

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Authors: Ye. V. Lyubun

Abstract:

The problem of agricultural-soil pollution is closely linked to the production of ecologically pure foodstuffs and to human health. An important task, therefore, is to rehabilitate agricultural soils with the help of state-of-the-art biotechnologies, based on the use of metal-accumulating plants. In this work, on the basis of literature data and the results of prior research from this laboratory, plants were selected for which the growing technology is well developed and which are widespread locally: sugar sorghum (Sorghum saccharatum), sudangrass (Sorghum sudanense (Piper.) Stapf.), and sunflower (Helianthus annuus L.). I report on laboratory experiments designed to study the influence of synthetic indole-3- acetic acid and the extracellular indole-3-acetic acid released by the plant-growth-promoting rhizobacterium Azospirillum brasilense Sp245 on growth of and arsenic accumulation by these plants.

Keywords: Arsenic, bioaccumulation, plant-growth-promoting rhizobacteria, phytohormones.

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Authors: N.Pourmahmoud, S.Akhesmeh

Abstract:

This work has been carried out in order to provide an understanding of the physical behaviors of the flow variation of pressure and temperature in a vortex tube. A computational fluid dynamics model is used to predict the flow fields and the associated temperature separation within a Ranque–Hilsch vortex tube. The CFD model is a steady axisymmetric model (with swirl) that utilizes the standard k-ε turbulence model. The second–order numerical schemes, was used to carry out all the computations. Vortex tube with a circumferential inlet stream and an axial (cold) outlet stream and a circumferential (hot) outlet stream was considered. Performance curves (temperature separation versus cold outlet mass fraction) were obtained for a specific vortex tube with a given inlet mass flow rate. Simulations have been carried out for varying amounts of cold outlet mass flow rates. The model results have a good agreement with experimental data.

Keywords: Ranque–Hilsch vortex tube, Temperature separation, k–ε model, cold mass fraction.

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Authors: Leehter Yao, Chin-Chin Lin

Abstract:

An adaptive fuzzy PID controller with gain scheduling is proposed in this paper. The structure of the proposed gain scheduled fuzzy PID (GS_FPID) controller consists of both fuzzy PI-like controller and fuzzy PD-like controller. Both of fuzzy PI-like and PD-like controllers are weighted through adaptive gain scheduling, which are also determined by fuzzy logic inference. A modified genetic algorithm called accumulated genetic algorithm is designed to learn the parameters of fuzzy inference system. In order to learn the number of fuzzy rules required for the TSK model, the fuzzy rules are learned in an accumulated way. In other words, the parameters learned in the previous rules are accumulated and updated along with the parameters in the current rule. It will be shown that the proposed GS_FPID controllers learned by the accumulated GA perform well for not only the regular linear systems but also the higher order and time-delayed systems.

Keywords: Gain scheduling, fuzzy PID controller, adaptive control, genetic algorithm.

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Authors: Pavan K. Emani, Shashank Kothari, V. S. Phanikanth

Abstract:

The ultimate load analysis of RC pile groups has assumed a lot of significance under liquefying soil conditions, especially due to post-earthquake studies of 1964 Niigata, 1995 Kobe and 2001 Bhuj earthquakes. The present study reports the results of numerical simulations on pile groups subjected to monotonically increasing lateral loads under design amounts of pile axial loading. The soil liquefaction has been considered through the non-linear p-y relationship of the soil springs, which can vary along the depth/length of the pile. This variation again is related to the liquefaction potential of the site and the magnitude of the seismic shaking. As the piles in the group can reach their extreme deflections and rotations during increased amounts of lateral loading, a precise modeling of the inelastic behavior of the pile cross-section is done, considering the complete stress-strain behavior of concrete, with and without confinement, and reinforcing steel, including the strain-hardening portion. The possibility of the inelastic buckling of the individual piles is considered in the overall collapse modes. The model is analysed using Riks analysis in finite element software to check the post buckling behavior and plastic collapse of piles. The results confirm the kinds of failure modes predicted by centrifuge test results reported by researchers on pile group, although the pile material used is significantly different from that of the simulation model. The extension of the present work promises an important contribution to the design codes for pile groups in liquefying soils.

Keywords: Collapse load analysis, inelastic buckling, liquefaction, pile group.

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Authors: YuriyTasinkevych, Ihor Trots, AndrzejNowicki, Marcin Lewandowski

Abstract:

The paper presents the optimization problem for the multi-element synthetic transmit aperture method (MSTA) in ultrasound imaging applications. The optimal choice of the transmit aperture size is performed as a trade-off between the lateral resolution, penetration depth and the frame rate. Results of the analysis obtained by a developed optimization algorithm are presented. Maximum penetration depth and the best lateral resolution at given depths are chosen as the optimization criteria. The optimization algorithm was tested using synthetic aperture data of point reflectors simulated by Filed II program for Matlab® for the case of 5MHz 128-element linear transducer array with 0.48 mm pitch are presented. The visualization of experimentally obtained synthetic aperture data of a tissue mimicking phantom and in vitro measurements of the beef liver are also shown. The data were obtained using the SonixTOUCH Research systemequipped with a linear 4MHz 128 element transducerwith 0.3 mm element pitch, 0.28 mm element width and 70% fractional bandwidth was excited by one sine cycle pulse burst of transducer's center frequency.

Keywords: synthetic aperture method, ultrasound imaging, beamforming.

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Authors: Hidehiko Okada, Jumpei Tokida

Abstract:

Researchers have been applying tional intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI methods with respect to each game application. In th our experimental result on the comparison of three evolutionary algorithms – evolution strategy, genetic algorithm, and their hybrid applied to evolving controller agents for the CIG 2007 Simulated Car Racing competition. Our experimental result shows that, premature convergence of solutions was observed in the case of ES, and GA outperformed ES in the last half of generations. Besides, a hybrid which uses GA first and ES next evolved the best solution among the whole solutions being generated. This result shows the ability of GA in globally searching promising areas in the early stage and the ability of ES in locally searching the focused area (fine-tuning solutions).

Keywords: Evolutionary algorithm, autonomous agent, neuroevolutions, simulated car racing.

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Authors: Francisca Grimón, Marylin Giugni, Josep Monguet F., Joaquín Fernández, Luis León G.

Abstract:

In blended learning environments, the Internet can be combined with other technologies. The aim of this research was to design, introduce and validate a model to support synchronous and asynchronous activities by managing content domains in an Adaptive Hypermedia System (AHS). The application is based on information recovery techniques, clustering algorithms and adaptation rules to adjust the user's model to contents and objects of study. This system was applied to blended learning in higher education. The research strategy used was the case study method. Empirical studies were carried out on courses at two universities to validate the model. The results of this research show that the model had a positive effect on the learning process. The students indicated that the synchronous and asynchronous scenario is a good option, as it involves a combination of work with the lecturer and the AHS. In addition, they gave positive ratings to the system and stated that the contents were adapted to each user profile.

Keywords: Blended Learning, System Adaptive, Model, Clustering Algorithms.

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Authors: Tian Hai, Yang Shengsheng, Jr., Wang Yi

Abstract:

Based on an analysis of the mechanism of degradation of optical characteristics of the ZnO-pigmented white paint by electron irradiation, a model of single molecular color centers is built. An equation that explains the relationship between the changes of variation of the ZnO-pigmented white paint-s spectrum absorptance and electron fluence is derived. The uncertain parameters in the equation can be calculated using the curve fitting by experimental data. The result indicates that the model can be applied to predict the degradation of optical characteristics of ZnO-pigmented white paint by electron radiation.

Keywords: ZnO-pigmented white pain, effects of electron radiation, optical characteristics degradation, prediction model.

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Authors: Zuodong Liang, Dong-Sheng Jeng

Abstract:

Seabed instability around an offshore pipeline is one of key factors that need to be considered in the design of offshore infrastructures. Unlike previous investigations, a three-dimensional numerical model for the wave-induced soil response around an offshore pipeline is proposed in this paper. The numerical model was first validated with 2-D experimental data available in the literature. Then, a parametric study will be carried out to examine the effects of wave, seabed characteristics and confirmation of pipeline. Numerical examples demonstrate significant influence of wave obliquity on the wave-induced pore pressures and the resultant seabed liquefaction around the pipeline, which cannot be observed in 2-D numerical simulation.

Keywords: Pore pressure, 3D wave model, seabed liquefaction, pipeline.

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Authors: Aboagela Dogman, Reza Saatchi, Samir Al-Khayatt

Abstract:

In this study, a network quality of service (QoS) evaluation system was proposed. The system used a combination of fuzzy C-means (FCM) and regression model to analyse and assess the QoS in a simulated network. Network QoS parameters of multimedia applications were intelligently analysed by FCM clustering algorithm. The QoS parameters for each FCM cluster centre were then inputted to a regression model in order to quantify the overall QoS. The proposed QoS evaluation system provided valuable information about the network-s QoS patterns and based on this information, the overall network-s QoS was effectively quantified.

Keywords: Fuzzy C-means; regression model, network quality of service

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

Abstract:

The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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Authors: Halil Snopce, Ilir Spahiu, Lavdrim Elmazi

Abstract:

A lot of Scientific and Engineering problems require the solution of large systems of linear equations of the form bAx in an effective manner. LU-Decomposition offers good choices for solving this problem. Our approach is to find the lower bound of processing elements needed for this purpose. Here is used the so called Omega calculus, as a computational method for solving problems via their corresponding Diophantine relation. From the corresponding algorithm is formed a system of linear diophantine equalities using the domain of computation which is given by the set of lattice points inside the polyhedron. Then is run the Mathematica program DiophantineGF.m. This program calculates the generating function from which is possible to find the number of solutions to the system of Diophantine equalities, which in fact gives the lower bound for the number of processors needed for the corresponding algorithm. There is given a mathematical explanation of the problem as well. Keywordsgenerating function, lattice points in polyhedron, lower bound of processor elements, system of Diophantine equationsand : calculus.

Keywords: generating function, lattice points in polyhedron, lower bound of processor elements, system of Diophantine equations and calculus.

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Authors: Yanling Zhu, Kai Wang

Abstract:

In this paper, by utilizing the coincidence degree theorem a predator-prey model with modified Leslie-Gower Hollingtype II schemes and a deviating argument is studied. Some sufficient conditions are obtained for the existence of positive periodic solutions of the model.

Keywords: Predator-prey model, Holling II type functional response, positive periodic solution, coincidence degree theorem.

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Authors: A. Larabi, M. S. Boucherit

Abstract:

In this paper, we show that the association of the PI regulators for the speed and stator currents with a control strategy using the linearization by state feedback for an induction machine without speed sensor, and with an adaptation of the rotor resistance. The rotor speed is estimated by using the model reference adaptive system approach (MRAS). This method consists of using two models: The first is the reference model and the second is an adjustable one in which two components of the stator flux, obtained from the measurement of the currents and stator voltages are estimated. The estimated rotor speed is then obtained by canceling the difference between stator-flux of the reference model and those of the adjustable one. Satisfactory results of simulation are obtained and discussed in this paper to highlight the proposed approach.

Keywords: Asynchronous actuator, PI Regulator, adaptivemethod with reference model, Vector control.

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