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2011
3
4
82
Using Identity-based Secret Public Keys Cryptography for Heuristic Security Analyses in Grid Computing
Using Identity-based Secret Public Keys Cryptography for Heuristic Security Analyses in Grid Computing
en
en
The majority of current security architectures for grid systems use public key infrastructure (PKI) to authenticate identities of grid members and to secure resource allocation to these members. Identity-based secret public keys have some attractive properties which seem to align well with the demands of grid computing. In this Paper, we proposed identity-based secret public keys. Our new identity-based approach allows secret public keys to be constructed in a very natural way using arbitrary random strings, eliminating the structure found in, for example, RSA or Diffie-Hellman keys. We examine identity-based secret public key protocols and give informal security analyses which show that they may well be secure against online password guessing and other attacks. More importantly, we present an identity-based secret public key version of the standard TLS protocol. Our new protocol allows passwords to be tied directly to the establishment of secure TLS channels.
357
375
Seyed Hossein
Kamali
Maysam
Hedayati
Reza
Shakerian
Saber
Ghasempour
Grid Computing
ID-SPK
Three-Party
Two-Party ID-SPK
TLS Protocol
Key exchange.
Article.1.pdf
[
[1]
I. Foster, C. Kesselman, The grid in a nutshell, in: Grid Resource Management, 2004 (2004), 3-13
##[2]
L. Gong, T. M. A. Lomas, R. M. Needham, J. H. Saltzer, Protecting poorly chosen secrets from guessing attacks, IEEE Journal on Selected Areas in Communications, 11 (1993), 648-656
##[3]
J. N. Luo, S. Shieh, J. C. Shen, Secure Authentication Protocols Resistant to Guessing Attacks, Journal of information science and engineering, 22 (2006), 1125-1143
##[4]
Y. Ding, P. Horster, Undetectable on-line password guessing attacks, ACM Operating Systems Review, 29 (1995), 77-86
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S. Patel, Number theoretic attacks on secure password schemes, Proceedings of the 1997 IEEE Symposium on Security and Privacy, 1997 (1997), 236-247
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M. Bellare, P. Rogaway, Optimal asymmetric encryption, Workshop on the Theory and Application of of Cryptographic Techniques, 1995 (1995), 92-111
##[7]
M. Steiner, P. Buhler, T. Eirich, M. Waidner, Secure password-based cipher suite for TLS, ACM Transactions on Information and System Security, 4 (2001), 134-157
##[8]
M. Abdalla, O. Chevassut, D. Pointcheval, One-time verifier-based encrypted key exchange, International Workshop on Public Key Cryptography, 2005 (2005), 47-64
##[9]
M. Abdalla, P. Fouque, D. Pointcheval, Password-based authenticated key exchange in the three-party setting, International Workshop on Public Key Cryptography, 2005 (2005), 65-84
##[10]
M. Abdalla, D. Pointcheval, Simple password-based encrypted key exchange protocols, Cryptographers’ track at the RSA conference, 2005 (2005), 191-208
##[11]
S. S. Al-Riyami, K. G. Paterson, Certificateless public key cryptography, International Conference on the Theory and Application of Cryptology and Information Security, 2003 (2003), 452-473
##[12]
M. Bellare, A. Boldyreva, A. Desai, D. Pointcheval, Key-privacy in public-key encryption, International Conference on the Theory and Application of Cryptology and Information Security, 2001 (2001), 566-582
##[13]
M. Bellare, D. Pointcheval, P. Rogaway, Authenticated key exchange secure against dictionary attacks, International conference on the theory and applications of cryptographic techniques, 2000 (2000), 139-155
##[14]
D. Boneh, M. Franklin, Identity-based encryption from the Weil pairing, Annual international cryptology conference, 2001 (2001), 213-229
##[15]
C. Boyd, A. Mathuria, Protocols for Authentication and Key Establishment, Springer-Verlag, Berlin (2003)
##[16]
K. Brincat, On the use of RSA as a secret key cryptosystem, Designs, Codes, and Cryptography, 22 (2001), 317-329
##[17]
D. Chaum, E. V. Heijst, B. Pfitzmann, Cryptographically strong undeniable signatures, unconditionally secure for the signer, Annual International Cryptology Conference, 1991 (1991), 470-484
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M. E. Hellman, S. C. Pohlig, Exponentiation Cryptographic Apparatus and Method, U.S. Patent (No. 4,424,414), Washington (1984)
##[19]
B. Libert, J-J. Quisquater, Efficient signcryption with key privacy from gap Diffie-Hellman groups, International Workshop on Public Key Cryptography, 2004 (2004), 187-200
##[20]
F. Zhang, W. Susilo, Y. Mu, Identity-based partial message recovery signatures (or how to shorten ID-based signatures), International Conference on Financial Cryptography and Data Security, 2005 (2005), 45-56
##[21]
Y. Zheng, Digital signcryption or how to achieve cost (signature & encryption)≪ cost (signature)+ cost (encryption), Annual International Cryptology Conference, 1997 (1997), 165-179
##[22]
T. Dierks, C. Allen, The TLS protocol version 1.0, The Internet Engineering Task Force (IETF), U.S.A. (1999)
]
Variational Monte Carlo Algorithm for Solving One Dimensional Harmonic Oscillator Problem
Variational Monte Carlo Algorithm for Solving One Dimensional Harmonic Oscillator Problem
en
en
The goal of this paper is to present an application of variational Monte Carlo method for solving one dimensional harmonic oscillator problem.
376
381
Farshid
Mehrdoust
Hossein
Aminikhah
Mohammad
Ghamgosar
Variational Monte Carlo (VMC)
Harmonic oscillator
quantum mechanical systems
Statistical physics.
Article.2.pdf
[
[1]
K. Binder, D. W. Heermann, Monte Carlo Simulations in Statistical Physics, Springer, Berlin (1988)
##[2]
W. M. C. Foulkes, L. Mitas, R. J. Needs, G. Rajagopal, Quantum Monte Carlo simulations of solids, Rev. Mod. Phys., 73 (2001), 33-83
##[3]
S. Pottorf, A. Pudzer, M. Y. Chou, J. E. Hasbun, The simple harmonic oscillator ground state using a variational Monte Carlo method, European journal of physics, 20 (1999), 250-212
]
Solving of Nonlinear System of Fredholm-volterra Integro-differential Equations by Using Discrete Collocation Method
Solving of Nonlinear System of Fredholm-volterra Integro-differential Equations by Using Discrete Collocation Method
en
en
In this paper, we solve nonlinear system of Fredholm-Volterra integro-differential equations by using discrete collocation method. These types of systems of integral equations are important and they can be used in engineering and some of the applied sciences such as population dynamics, reaction-diffusion in small cells and models of epidemic diffusion. Also these equations with convolution kernel can be solved by discrete collocation method. By the above mentioned method we approximate solution of equation by no smooth piecewise polynomials, for validity and ability the method we solve some examples with high accuracy.
382
389
M.
Rabbani
S. H.
Kiasoltani
Fredholm-Volterra integro-differential equations
discrete collocation method
Article.3.pdf
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[1]
K. E. Atkinson, The Numerical Solution of Integral Equations of the Second Kind, Cambridge University Press, Cambridge (1997)
##[2]
A. Ayad, Spline approximation for first order Fredholm integro-differential equations, Studia Univ. Babes-Bolyai Math., 41 (1996), 1-8
##[3]
H. Brunner, Collocation Method for Volterra Integral and Related Functional Equations, Cambridge University Press, Combridge (2004)
##[4]
M. Lakestani, M. Razzaghi, M. Dehghan, Semiorthogonal spline wavelets approximation for Fredholm integro-differential equations, Math. Probl. Eng., 2006 (2006), 1-12
##[5]
C. Lubich, Convolution Quadrature and Discretized Operational Calculus II, Numerische Mathematik, 52 (1988), 413-425
##[6]
K. Maleknejad, M. Karami, Using the WPG method for Solving Integral equations of the second kind, Appl. Math. Comput., 166 (2005), 123-130
##[7]
M. Rabbani, K. Maleknejad, N. Aghazadeh, Numerical computational solution of the volterra integral system of the second kind by using an expansion method, Applied Mathematics and Computation, 187 (2007), 1143-1146
##[8]
K. Maleknejad, M. Rabbani, N. Aghazadeh, M. Karami, A wavelet Petrov–Galerkin method for solving integro-differential equations, International Journal of Computer Mathematics, 86 (2009), 1572-1590
]
Decision-making for a Single Item EOQ Model with Demand-dependent Unit Cost and Dynamic Setup Cost
Decision-making for a Single Item EOQ Model with Demand-dependent Unit Cost and Dynamic Setup Cost
en
en
A Single item EOQ model is modeled using crisp arithmetic approach in decision making
process with demand unit cost and dynamic setup cost varies with the quantity
produced/Purchased. This paper considers the modification of objective function and storage
area in the presence of estimated parameters. The model is developed for the problem by
employing NLP modeling approaches over an infinite planning horizon. It incorporates all
concepts of crisp arithmetic approach, the quantity ordered, the demand per unit and compares
with other model that of the crisp would optimal ordering policy of the problem over an infinite
time horizon is also suggested. Investigation of the properties of an optimal solution allows
developing an algorithm for obtaining solution through LINGO 13.0 version whose validity is
illustrated through an example problem. Sensitivity analysis of the optimal solution is also
studied with respect to changes in different parameter values and to draw managerial insights.
390
395
M.
Pattnaik
Single item
EOQ
Unit cost
Dynamic setup cost
Article.4.pdf
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T. C. E. Cheng, An economic order quantity model with demand-dependent unit cost, Eur. J. Oper. Res., 40 (1989), 252-256
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G. U. Tinarelli, Inventory control models and problems, Eur. J. Oper. Res., 14 (1983), 1-12
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T. M. Whitin, Inventory control research and survey, Manag. Sci., 1 (1954), 32-40
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T. K. Roy, M. Maiti, A fuzzy EOQ model with demand dependent unit cost under limited storage capacity, Eur. J. Oper. Res., 99 (1997), 425-432
##[5]
T. K. Roy, M. Maity, A fuzzy inventory model with constraint, Operational Research Society of India, 32 (1995), 287-298
##[6]
P. K. Tripathy, M. Pattnaik, Optimal inventory policy with reliability consideration and instantaneous receipt under imperfect production process, International Journal of Management Science and Engineering Management, 6 (2011), 413-420
##[7]
P. K. Tripathy, M. Pattnaik, Optimization in an inventory model with reliability consideration, Appl. Math. Sci., 3 (2009), 11-25
##[8]
M. Pattnaik, Entropic order quantity (EnOQ) model under Cash Discounts, Thailand Statistician journal, 9 (2011), 129-141
##[9]
P. K. Tripathy, M. Pattnaik, An fuzzy arithmetic approach for perishable items in discounted entropic order quantity model, International Journal of Scientific and Statistical Computing, 1 (2011), 7-19
##[10]
A. J. Clark, An informal survey of multi echelon inventory theory, Naval Research Logistics Quarterly, 19 (1972), 621-650
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G. Hadley, T. M. Whitin, Analysis of inventory systems, Prentice-Hall, Englewood Clipps (1963)
##[12]
H. A. Taha, Operations Research: an introduction, Macmilliion, New York (1976)
]
Determining the Objective Value Range for a Class of Interval Convex Optimization Problems
Determining the Objective Value Range for a Class of Interval Convex Optimization Problems
en
en
This paper generalizes a method of determining the objective value range of
quadratic programming problems to a general class of interval convex programming ones,
where all coefficients in objective function and constraints are interval numbers. The upper
bound and lower bound of the objective values of the interval quadratic program is
calculated by formulating a pair of two-level mathematical programs. Based on the duality
theorem and by applying the variable transformation technique, the pair of two-level
mathematical programs is transformed into conventional one-level convex programming
problem. Solving the pair of convex programs produces the interval of the objective values
of the problem. Numerical results confirms the procedure of the presented approach.
396
402
Akbar
Hashemi Borzabadi
Leila
Heidarian
Interval convex programming
Interval parameters
Two-level program.
Article.5.pdf
[
[1]
S. A. Abass, An interval number programming approach for bilevel linear programming problem, International Journal of Management Science and Engineering Management, 5 (2010), 461-464
##[2]
M. S. Bazaraa, H. D. Sherali, C. M. Shetty, Nonlinear Programming: Theory and Algorithm, John Wiley & Sons, New York (1993)
##[3]
M. F. Cao, G. H. Huang, L. He, An approach to interval programming problems with left-hand-side stochastic coefficients: An application to environmental decisions analysis, Expert Syst. Appl., 38 (2011), 11538-11546
##[4]
H. Ishibuchi, H. Tanaka, Multiobjective programming in optimization of the interval objective function, Eur. J. Oper. Res., 48 (1990), 219-225
##[5]
V. I. Levin, Ordering of Intervals and Optimization Problems with Interval Parameters, Cybernetics and Systems Analysis, 40 (2004), 316-324
##[6]
K. K. Lai, S. Y. Wang, J. P. Xu, S. S. Zhu, Y. Fang, A class of linear interval programming problems and its application to portfolio selection, IEEE Transactions on Fuzzy Systems, 10 (2002), 698-704
##[7]
W. Li, X. Tian, Numerical solution method for general interval quadratic programming, Applied Mathematics and Computation, 202 (2008), 589-595
##[8]
S.-T. Liu, R.-T. Wang, A numerical solution method to interval quadratic programming, Applied Mathematics and Computation, 189 (2007), 1274-1281
##[9]
H.-C. Wu, The Karush-Kuhn-Tucker optimality conditions in an optimization problem with interval-valued objective function, Eur. J. Oper. Res., 176 (2007), 46-59
##[10]
H. -C. Wu, On interval-valued nonlinear programming problems, J. Math. Anal. Appl., 338 (2008), 299-316
]
Bernstein Polynomials for Solving Abels Integral Equation
Bernstein Polynomials for Solving Abels Integral Equation
en
en
This paper presents a numerical method for solving Abel’s integral equation as singular Volterra integral equations. In the proposed method, the functions in Abel’s integral equation are approximated based on Bernstein polynomials (BPs) and therefore, the solving of Abel’s integral equation is reduced to the solving of linear algebraic equations. Illustrative examples are included to demonstrate the validity and applicability of the technique.
403
412
Mohsen
Alipour
Davood
Rostamy
Abel’s integral equations
Singular Volterra integral equations
Bernstein polynomials.
Article.6.pdf
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[1]
R. Goreno, S. Vessella, Abel integral equations: analysis and applications, Springer-Verlag, Berlin-New York (1991)
##[2]
N. Zeilon , Sur quelques points de la theorie de l’equation integrale d’Abel, Arkiv. Mat. Astr. Fysik. , 18 (1922), 1-19
##[3]
F. G. Tricomi, Integral Equations, Dover Publications, New York (1985)
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L. J. Lardy, A variation of Nystrom’s method for Hammerstein equations, J. Integ. Equat., 3 (1981), 43-60
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S. Kumar, I. H. Sloan, A new collocation-type method for Hammerstein integral equations, J. Math. Comput., 48 (1987), 123-129
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H. Brunner, Implicitly linear collocation method for nonlinear Volterra equations, J. Appl. Num. Math., 9 (1992), 235-247
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H. Guoqiang, Asymptotic error expansion variation of a collocation method for Volterra–Hammerstein equations, J. Appl. Num. Math., 13 (1993), 357-369
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P. Baratella, A. P. Orsi, A new approach to the numerical solution of weakly singular Volterra integral equations, J. Computat. Appl. Math., 163 (2004), 401-418
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E. Kreyszig, Introduction Functional Analysis with Applications, John Wiley & Sons, U.S.A. (1978)
##[10]
A. M. Wazwaz, A First Course in Integral Equations, World Scientific Publishing Company, New Jersey (1997)
]
Relationship Between Organizational Intelligence and Entrepreneurship Among University Educational Managers
Relationship Between Organizational Intelligence and Entrepreneurship Among University Educational Managers
en
en
Entrepreneurship is one of the important resources in all human societies regarded as one of the most important assets for each country. In todays complicated world those organizations are more important that are having human resources withrich intelligence. This study probes to find the relationship between organizational intelligence and entrepreneurship from the view point of educational managers of Mazandaran University. To this purpose a number of 202 managers were selected through census. This study is descriptive- correlational in nature and the instruments used for data collection are Albercht’s Organizational Intelligence questionnaire and Robbins’ entrepreneurship questionnaire. Data was analyzed through Pearson Correlation Coefficient, stepwise regression and structural equations were used to find out the relationship between variables. Results of regression analysis showed alignment and congruence had the most direct effect on entrepreneurship,( β = 0.39, P <0.01) and after that heart and appetite for change come. Other variables also have effects on entrepreneurship indirectly and through these three variables. The most indirect effect of variables on dependent variable is pertinent to the performance pressure ( β = 0.28) .The analytical model developed in this study for the relationship between variables shows high correlation between organizational intelligence and entrepreneurship.
413
421
A.
Bakhshian
F.
Hamidi
M.
Ezati
organizational intelligence
entrepreneurship
educational managers
Article.7.pdf
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[1]
B. Antoncic, I. Prodan, Alliances, corporate technological entrepreneurship and firm performance: Testing a model on manufacturing firms, Technovation, 28 (2008), 257-265
##[2]
M. Abzari, M. Sattari Ghahfarkhi, Relationship between Knowledge Management Sub-System in Learning Organization and Organizational Intelligence Components, The First National Conference of Knowledge Management , Iran (2007)
##[3]
M. Ahmadpour Dariani, Design and Description of Training Entrepreneur Managers in Industry, Thesis for Ph.D. (Tarbiat Modarres University), Tehran (1999)
##[4]
K. Albrecht, Organizational intelligence survey preliminaryAssessment, Journal Institute Of Management, 2003 (2003), 1-7
##[5]
K. Albrecht, The Power of minds at work: organizational intelligence in action, American Management, U.S.A. (2003)
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R. Amit, L. Glosten, E. Muller, Challenges to theory development in entrepreneurship research, Journal of Management Studies, 30 (1993), 815-834
##[7]
M. Ashena, A. Marzban, M. Taslimi, Relationship between Social Capital and Organization Enterpreneurship, Farhang Modiriat Publication, Tehran (1997)
##[8]
J. R. Baum, B. J. Bird, S. Singh, The practical intelligence of entrepreneurs: Antecedents and a link with new venture growth, Personnel Psychology, 64 (2011), 397-425
##[9]
C. W. Choo, Information management for an intelligent-organization: The art of environmental scanning, Learned Information, Medford (1995)
##[10]
W. E. Halal, Organizational Intelligence: What is it, and how can managers use it?, http://www. strategy-business. com/article/12644, U.S.A. (1997)
##[11]
W. E. Halal, Organization Intelligence, Melcrum publishing Ltd., U. K. (2006)
##[12]
V. Lefter, M. Prejmerean, S. Vasilache, The dimensions of organizational intelligence in Romanian companies–a human capital perspective, Academy of Economic Studies.Bucharest, 10 (2008), 39-52
##[13]
J. Liebowitz, Entrepreneurship: Next century’s university funding will come mostly from successful entrepreneur alumni, Manag. rev., 147 (2005), 128-136
##[14]
T. Matsuda, Organizational Intelligence:Its Significance as a Process and as a Product, Procceding of the International Conferencw on Economics/Management and Information Technology (Tokyo), Japan (1992)
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S. M. Moghimi, A research Approach to: Organization and Management, Termeh Publication, 2008 (2008), 160-162
##[16]
A. Ruhan, J. C. Iijima, H. Sho, A Study on Relationship between Organization Intelligence Quotient and Firm Performance, Tokyo Institute of Technology, Japan (2009)
##[17]
A. Ruhan, J. C. Iijima, H. Sho, A Study on Relationship between Organization Intelligence Quotient and Firm Performance, Tokyo Institute of Technology, Japan (2009)
##[18]
M. Schwaninger, Intelligent organizations: an integrative framework, The Official Journal of the International Federation for Systems Research, 18 (2001), 137-158
##[19]
H. H. Frederick, D. F. Kuratko, R. M. Hodgetts, Entrepreneurship: theory, process, practice, South-Western College Pub., U.S.A. (2004)
##[20]
J. J. Vanvuuren, An action learning approach to entrepreneurial creativity, innovation and opportunity finding, Doctoral dissertation (University of Pretoria), Pretoria (2003)
##[21]
R. Veryard , Component-Based Business Background Material-Business Patterns, CBDi Forum journal, 2000 (2000), 1-11
]
New Approach for Solving of Linear Fredholm Fuzzy Integral Equations Using Sinc Function
New Approach for Solving of Linear Fredholm Fuzzy Integral Equations Using Sinc Function
en
en
A numerical method is proposed to solve linear fredholm fuzzy integral equations(LFFIE). The proposed method in this paper is based on concept of the
parametric form of fuzzy numbers and Sinc wavelet. By using the parametric
form of fuzzy numbers linear fredholm fuzzy integral equations have been converted into a system of fredholm integral equations in the crisp form, and Sinc
approach this problem reduced to solving algebraic equations. The efficiency of
the proposed approach is demonstrated by numerical examples.
422
431
Mohammad
Keyanpour
Tahereh
Akbarian
Sinc function
Linear fredholm fuzzy integral equation
Fuzzy parametric form.
Article.8.pdf
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[1]
R. E. Bellman, R. Kalaba, L. A. Zadeh, Abstraction and Pattern Classification, RAND Memo, 19 pages, (1964)
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S. C. Arora, V. Sharma, Fixed point theorems for fuzzy mappings, Fuzzy Sets and Systems, 110 (2000), 127-130
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J. Y. Park, J. U. Jeong, Fixed point theorems for fuzzy mappings, Fuzzy Sets and Systems, 87 (1997), 111-116
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V. Lakshmikantham, A. S. Vatsala, Existence of fixed points of fuzzy mappings via theory of fuzzy differential equations, J. Comput. Appl. Math., 113 (2000), 195-200
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M. Ghanbari, R. Toushmalni, E. Kamrani, Numerical solution of linear Fredholm fuzzy integral equation of the second kind by Block-pulse functions, Aust. J. Basic Appl. Sci., 3 (2009), 2637-2642
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T. Allahviranlooa, S. Hashemzehi, The Homotopy Perturbation Method for Fuzzy Fredholm Integral Equations, Journal of Applied Mathematics, Vol. 5, 1--12, (2008)
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M. Friedman, M. Ma, A. Kandel, Numerical solutions of fuzzy differential and integral equations, Fuzzy Sets and Systems, 106 (1999), 35-48
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H. S. Goghary, M. S. Goghary, Two computational methods for solving linear Fredholm fuzzy integral equation of te second kind, Applied Mathematics And Computation , 182 (2006), 791-796
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S. Abbasbandy, E. Babolian, M. Alavi, Numerical method for solving linear Fredholm fuzzy integral equations of the second kind, Chaos Solitons Fractals, 31 (2007), 138-146
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O. S. Fard, M. Sanchooli, Two Successive Schemes for Numerical Solution of Linear Fuzzy Fredholm Integral Equations of the Second Kind Australian , Australian Journal of Basic and Applied Sciences, 4 (2010), 817-825
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A. Molabahrami, A. Shidfar, A. Ghyasi, An analytical method for solving linear Fredholm fuzzy integral equations of the second kind, Computers and Mathematics with Applications , 61 (2011), 2754-2761
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K. Maleknejad, R. Mollapourasl, P. Torabi, M. Alizadeh, Solution of First kind Fredholm Integral Equation by Sinc Function, World Academy of Science, Engineering and Technology, 1539--1543 (2010)
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E. Babolian, H. Sadeghi Goghary, S. Abbasbandy, Numerical solution of linear Fredholm fuzzy integral equations of the second kind by Adomian method, Appl. Math. Comput., 161 (2005), 733-744
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M. Annunziato, A. Borzi, Fast solvers of Fredholm optimal control problems, Numerical Mathematics: Theory, Methods and Applications, 3 (2010), 431-448
]
On Critical Exponent for the Existence and Multiplicity of Positive Weak Solutions for a Class of (p, Q)-laplacian Nonlinear System
On Critical Exponent for the Existence and Multiplicity of Positive Weak Solutions for a Class of (p, Q)-laplacian Nonlinear System
en
en
In this paper, we prove the existence of positive weak solution for the nonlinear elliptic system
\[
\begin{cases}
-\Delta_p u=\lambda_1u^a+\mu_1v^b,\,\,\,\,\, x\in\Omega,\\
-\Delta_q v=\lambda_2u^c+\mu_2v^d,\,\,\,\,\, x\in\Omega,\\
u=0=v,\,\,\,\,\, x\in \partial \Omega.
\end{cases}
\]
where \(\Delta_sz=div(|\nabla z|^{s-2}\nabla z), s>1, \lambda_1, \lambda_2, \mu_1\) and \(\mu_2\) are positive parameters, and \(\Omega\) is a
bounded domain in \(R^N, a + c < p - 1\) and \(b + d < q - 1\). We also discuss a multiplicity result
when \(0 < \lambda_1, \lambda_2, \mu_1, \mu_2<\lambda^* \) for some \(\lambda^* \). We obtain our results via the method of sub - and super
solutions.
432
439
M. B.
Ghaemi
G. A.
Afrouzi
S. H.
Rasouli
M.
Choubin
Positive weak solution
p-Laplacian
Sub - and super solutions.
Article.9.pdf
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[1]
J. Ali, R. Shivaji, Positive solutions for a class of p-Laplacian systems with multiple parameters, J. Math. Anal. Appl., 335 (2007), 1013-1019
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H. Amann, Fixed point equations and nonlinear eigenvalue problems in ordered Banach spaces, SIAM Rev., 18 (1976), 620-709
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C. Chen, On positive weak solutions for a class of quasilinear elliptic systems, Nonlinear Analysis: Theory, Methods & Applications, 62 (2005), 751-756
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##[6]
E. K. Lee, R. Shivaji, J. L. Ye, Positive solutions for elliptic equations involving nonlinearities with fallig zeroes, Appl. Math. Letters, 22 (2009), 846-851
##[7]
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]