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Search Results: 1 - 10 of 241 matches for " AKHILESH AYACHI "
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Journal of Applied Sciences in Environmental Sanitation , 2012,
Abstract: In the present study 212 specimens of wood decaying fungi were collected from Chhattisgarh, India, during survey in rainy season, 2009- 2010. These were identified, brought in pure culture by tissue culture method on Potato dextrose agar medium. Out of these, 33 species were screened and tested for cellulose degradation capability using filter paper cellulose. The ability of host fungus to utilize insoluble form of cellulose was measured. It was found that, all the 33 wood decaying fungi were able to decompose cellulose at varying degree. Biodegradation of cellulose and CAI were observed maximum with Navisporus floccosus whereas, Pyrofomes tricolor showing minimum biodegradation of cellulose and Flavodon flavus show minimum CAI. It is concluded that cellulose decomposition pattern was vary not only among the genera but also between the species of same genus.
La política exterior de Marruecos.
Mohammed Ayachi.
Colombia Internacional , 1992,
Neural Modeling of Multivariable Nonlinear Stochastic System. Variable Learning Rate Case  [PDF]
Ayachi Errachdi, Ihsen Saad, Mohamed Benrejeb
Intelligent Control and Automation (ICA) , 2011, DOI: 10.4236/ica.2011.23020
Abstract: The objective of this paper is to develop a variable learning rate for neural modeling of multivariable nonlinear stochastic system. The corresponding parameter is obtained by gradient descent method optimization. The effectiveness of the suggested algorithm applied to the identification of behavior of two nonlinear stochastic systems is demonstrated by simulation experiments.
A Comparative Study of Nonlinear Time-Varying Process Modeling Techniques: Application to Chemical Reactor  [PDF]
Errachdi Ayachi, Saad Ihsen, Benrejeb Mohamed
Journal of Intelligent Learning Systems and Applications (JILSA) , 2012, DOI: 10.4236/jilsa.2012.41002
Abstract: This paper proposes the design and a comparative study of two nonlinear systems modeling techniques. These two approaches are developed to address a class of nonlinear systems with time-varying parameter. The first is a Radial Basis Function (RBF) neural networks and the second is a Multi Layer Perceptron (MLP). The MLP model consists of an input layer, an output layer and usually one or more hidden layers. However, training MLP network based on back propagation learning is computationally expensive. In this paper, an RBF network is called. The parameters of the RBF model are optimized by two methods: the Gradient Descent (GD) method and Genetic Algorithms (GA). However, the MLP model is optimized by the Gradient Descent method. The performance of both models are evaluated first by using a numerical simulation and second by handling a chemical process known as the Continuous Stirred Tank Reactor CSTR. It has been shown that in both validation operations the results were successful. The optimized RBF model by Genetic Algorithms gave the best results.
Studies on Aluminum-Iron Ore in-Situ Particulate Composite  [PDF]
S. Sarkar, Akhilesh Singh
Open Journal of Composite Materials (OJCM) , 2012, DOI: 10.4236/ojcm.2012.21004
Abstract: Discontinuously reinforced aluminium matrix composites are fast emerging as engineering materials and competing with common metals and alloys. They are gaining significant acceptance because of higher specific strength, specific modulus and good wear resistance as compared to ordinary unreinforced alloys. Reinforcing particles or short fibers normally used are silicon carbide and alumina which are added externally. Recently it has been shown that alumina particles can be produced in-situ by reaction with metallic oxides reduced by aluminium. Alumina particles thus produced are dispersed in the aluminium matrix and the elementary metal gives solid solution strengthening of the matrix. In-situ particulate composites in comparison with conventional cast particulate composites produced by external addition promote cleaner interface, eliminates interface incompatibility of the matrices with the reinforcements, help to achieve greater thermodynamic stability of reinforcement particles in the matrix at elevated temperature and also increase the possibility of developing coherency between the matrix and particles formed in-situ. The morphology and the distribution of particles strongly influence the physical and mechanical properties of composites. In the present investigation, iron ore was added to molten aluminium, aluminium-magnesium and aluminium-silicon alloys by vortex method. The iron oxides present in the iron ore are observed to react with aluminium, magnesium resulting in production of Al2O3, MgO and metallic iron which dissolved in liquid aluminium. The composites thus produced were cast into cast iron die. The mechanical properties of the composites were evaluated. The dry sliding wear behavior of the cast composites was studied at different loads and different sliding velocities using Pin-On-Disk configuration wear testing machine. The worn surfaces and the wear debris were also analyzed using optical microscope and scanning electron microscope.
Simulating the Effect of Social Network Structure on Workflow Efficiency Performance  [PDF]
Akhilesh Bajaj, Sandip Sen
Social Networking (SN) , 2014, DOI: 10.4236/sn.2014.31004

The effect of social network structure on team performance is difficult to investigate using standard field observational studies. This is because social network structure is an endogeneous variable, in that prior team performance can influence the values of structural measures such as centrality and connectedness. In this work we propose a novel simulation model based on agent-based modeling that allows social network structure to be treated as an exogeneous variable but still be allowed to evolve over time. The simulation model consists of experiments with multiple runs in each experiment. The social network amongst the agents is allowed to evolve between runs based on past performance. However, within each run, the social network is treated as an exogenous variable where it directly affects workflow performance. The simulation model we describe has several inputs and parameters that increase its validity, including a realistic workflow management depiction and real-world cognitive strategies by the agents.

Variational Methods for Almost Periodic Solutions of a Class of Neutral Delay Equations
M. Ayachi,J. Blot
Abstract and Applied Analysis , 2008, DOI: 10.1155/2008/153285
Abstract: We provide new variational settings to study the a.p. (almost periodic)solutions of a class of nonlinear neutral delay equations. We extend Shu and Xu (2006) variational setting for periodic solutions of nonlinear neutral delay equation to the almost periodic settings. We obtain results on the structure of the set of the a.p. solutions, results of existence of a.p. solutions,results of existence of a.p. solutions, and also a density result for the forcedequations.
Integrated Area-power Optimal State Assignment
Akhilesh Tyagi
VLSI Design , 2001, DOI: 10.1155/2001/39405
Abstract: This paper presents a state assignment algorithm with the objective of lower energy along with area comparable to the area-targeting state assignments such as JEDI. The underlying framework is MUSTANG's complete weighted graph with weights representing state affinity. The weight computation phase estimates the computation energy of potential common cubes using steady state probabilities for transitions. The weight computation phase also identifies a large set of potential state cliques, which are incorporated into a recursive bipartitioning based state assignment procedure. Reuse of cliques identified by the weight computation phase results in a faster and efficient state assignment. The energy targeting weights result in ≈9% lower area and 18% lower power than area targeting weights in JEDI over 29 MCNC Logic Synthesis ‘93 benchmarks. The clique based state assignment performs almost as well as the annealing based state assignment in JEDI, and takes only about half as much time.
Efficacy of new fungicides In the management of early and late blight of potato
Indian Phytopathology , 2011,
Statistical Module Level Area and Delay Estimation
Akhilesh Tyagi
VLSI Design , 1997, DOI: 10.1155/1997/78238
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