eng
Shiraz University
Iranian Journal of Science and Technology (Sciences)
1028-6276
1028-6276
2010-12-01
34
4
275
283
10.22099/ijsts.2010.2178
2178
K-NACCI SEQUENCES IN MILLER’S GENERALIZATION OF POLYHEDRAL GROUPS
O. DEVECI
odeveci36@hotmail.com
1
O. KARADUMAN
2
Department of Mathematics, Faculty of Science and Letters, Kafkas University, Turkey
Ataturk University, Department of Mathematics, Faculty of Science, Erzurum, Turkey
A k-nacci sequence in a finite group is a sequence of group elements x0 , x1, x2 ,, xn , forwhich, given an initial (seed) set 0 1 2 1 , , , ,j x x x x , each element is defined by0 1 11 1for ,for .nnn k n k nxx x j n kxx x x n k In this paper, we examine the periods of the k-nacci sequences in Miller’s generalization of the polyhedralgroups 2,2 2;q , n,2 2;q , 2, n 2;q , 2,2 n;q , for any n 2 .
http://ijsts.shirazu.ac.ir/article_2178_dff494d682e14b56655c2b273c389f62.pdf
K-nacci sequence
period
dihedral group
polyhedral group
eng
Shiraz University
Iranian Journal of Science and Technology (Sciences)
1028-6276
1028-6276
2010-12-01
34
4
285
303
10.22099/ijsts.2010.2179
2179
QCD FACTORIZATION IN HADRONIC B J/ ( ,K) DECAYS*
H. MEHRBAN
hmehraban@semnan.ac.ir
1
M. SAYAHI
2
Physics Department, Semnan University, Semnan, I. R. of Iran
Physics Department, Semnan University, Semnan, I. R. of Iran
Using QCD factorization for the hadronic matrix elements, we show that existing data, inparticular the branching ratios BR ( B →J/ψK) and BR ( B →J/ψπ), can be accounted for in this approach.We analyze the decay B J /K( ) within the framework of QCD factorization. The calculation of therelevant hard-scattering kernels for twist-2 and twist-3 is completed. We calculate this decay in a special scale( mb ) and in two schemes for Wilson coefficients in NLO. We consider three functions for J / . Thetwist-3 contribution involves the logarithmically divergent integral, we consider H 0 the cancelingdivergent. The obtained results are in agreement with available experimental data.
http://ijsts.shirazu.ac.ir/article_2179_382ae7c78eb8fff892e5ab88b10b2907.pdf
B Meson
hard scattering
QCD factorization
2 and 3-twist
eng
Shiraz University
Iranian Journal of Science and Technology (Sciences)
1028-6276
1028-6276
2010-12-01
34
4
305
312
10.22099/ijsts.2010.2180
2180
SUBORBITAL GRAPHS FOR A SPECIAL SUBGROUP OF THE NORMALIZER OF m
S. KADER
1
O GULER
2
A. H. DEGER
3
Department of Mathematics, Nigde University, Nigde, Turkey
Department of Mathematics, Rize University, Rize, Turkey Email: bahadir.guler@rize.edu.tr
Department of Mathematics, Karadeniz Technical University, Trabzon, Turkey
In this paper, we find the number of sides of circuits in suborbital graph for the normalizer of0 (m) in PSL(2,), where m will be of the form 2p2 , p is a prime and p 1 mod 4. In addition, wegive a number theoretical result which says that the prime divisors p of 2u2 2u 1 are of the formp 1 mod 4.
http://ijsts.shirazu.ac.ir/article_2180_503b02bd26a76b5c216d53711c31cc33.pdf
In this paper
we find the number of sides of circuits in suborbital graph for the normalizer of
0 (m) in PSL(2
)
where m will be of the form 2p2
p is a prime and p 1 mod 4. In addition
we give a number theoretical result which says that the prime divisors p of 2u2 2u 1 are of the form p 1 mod 4
eng
Shiraz University
Iranian Journal of Science and Technology (Sciences)
1028-6276
1028-6276
2010-12-01
34
4
313
320
10.22099/ijsts.2010.2181
2181
A NOVEL NAVIGATION METHOD FOR PURSUING A MOVING TARGET
H. ATTARCHI
1
B. BIDABAD
bidabad@aut.ac.ir
2
M. M. REZAII
3
Faculty of Mathematics and Computer Sciences, Amirkabir University of Technology, 424 Hafez Ave, 15914 Tehran, I. R. of Iran
Faculty of Mathematics and Computer Sciences, Amirkabir University of Technology, 424 Hafez Ave, 15914 Tehran, I. R. of Iran
Faculty of Mathematics and Computer Sciences, Amirkabir University of Technology, 424 Hafez Ave, 15914 Tehran, I. R. of Iran
The most current pursuit algorithms for moving targets which are presented so far in the literatureare Pure Pursuit and Pure Rendezvous navigations. Recently, one of the present authors has introduced ageometric model for the Pure Pursuit navigation algorithm. Here, in this paper, we study a new algorithm forthe pursuit navigation problem which is a combination of both of the above algorithms. We study itsgeometric properties, as well as the trajectories as time optimal paths. Finally, we compare this algorithm withwell-known algorithms in some real examples.
http://ijsts.shirazu.ac.ir/article_2181_4bef8db34f486819627026bcbe6f6e61.pdf
Pure Pursuit
Pure Rendezvous
Composed Pursuit
Finsler metric
eng
Shiraz University
Iranian Journal of Science and Technology (Sciences)
1028-6276
1028-6276
2010-12-01
34
4
321
334
10.22099/ijsts.2010.2182
2182
TWO-DIRECTION POLY-SCALE REFINEMENT EQUATIONS WITH NONNEGATIVE COEFFICIENTS
S. YANG
szyang@stu.edu.cn
1
J. LIN
2
Department of Mathematics, Shantou University, Shantou, P. R. China
Department of Mathematics, Shantou University, Shantou, P. R. China
In this paper, we study L1 -solutions of the following two-direction poly-scale refinement equationWe prove that the vector space of all L1 -solutions of the above equation is at most one-dimensional andconsists of compactly supported functions of constant sign. We also show that any- L1 solution of the aboveequation is either positive or negative on its support under a special assumption. With regard to the -solutions of the equation, some simple sufficient conditions for the existence of nontrivial -solutions andthe nonexistence of such solutions are given.
http://ijsts.shirazu.ac.ir/article_2182_627de8f44897b33f1b0d477fdc205182.pdf
Two-direction poly-scale refinement equation
-solutions
iterated function systems
eng
Shiraz University
Iranian Journal of Science and Technology (Sciences)
1028-6276
1028-6276
2010-12-01
34
4
335
338
10.22099/ijsts.2010.2183
2183
STRONGLY SUMMABLE AND STATISTICALLY CONVERGENT FUNCTIONS
F. NURAY
fnuray@aku.edu.tr
1
Afyon Kocatepe University, Mathematics Department Afyonkarahisar, Turkey
In this study, by using the notion of (V, λ)-summability, we introduce and study the concepts of λ-strongly summable and λ-statistiacally convergent functions.
http://ijsts.shirazu.ac.ir/article_2183_b6adebce7f762589825df4487ebd4801.pdf
Statistical convergence
strongly summable function
eng
Shiraz University
Iranian Journal of Science and Technology (Sciences)
1028-6276
1028-6276
2010-12-01
34
4
339
348
10.22099/ijsts.2010.2184
2184
ON A CHARACTERISTIC PROBLEM FOR A THIRD ORDER PSEUDOPARABOLIC EQUATION
A. MAHER
a_maher69@yahoo.com
1
YE. A. UTKINA
2
Department of Mathematics, Faculty of Science, Assiut University, Egypt
Department of Differential Equations, Kazan State University, Kazan, Russia
In this paper, we investigate the Goursat problem in the class C21(D)Cn0 (D P) C00 (D Q)for a third order pseudoparabolic equation. Some results are given concerning the existence and uniquenessfor the solution of the suggested problem.
http://ijsts.shirazu.ac.ir/article_2184_fc1f37311a4ea8ca4d3e8db7181117e1.pdf
Third order pseudoparabolic equation
the Goursat problem
eng
Shiraz University
Iranian Journal of Science and Technology (Sciences)
1028-6276
1028-6276
2010-12-01
34
4
349
353
10.22099/ijsts.2010.2185
2185
TWO-PHASE SAMPLE SIZE ESTIMATION WITH PRE-ASSIGNED VARIANCE UNDER NORMALITY ASSUMPTION
M. SALEHI
salehi@qu.edu.qa
1
P. S. LEVY
2
J. RAO
3
Department of Mathematics, Statistics and Physics, Qatar University, Doha, Qatar Department of Mathematical Sciences, Isfahan University of Technology, Isfahan, I. R. of Iran
3RTI International, Research Triangle Park, North Carolina, USA
School of Mathematics and Statistics, Carleton University, Ottawa, Canada
We develop a two phase sampling procedure to determine the sample size necessary to estimatethe population mean of a normally distributed random variable and show that the resulting estimator has preassigned variance and is unbiased under a regular condition. We present a necessary and sufficient condition under which the final sample mean is an unbiased estimator for the population mean.
http://ijsts.shirazu.ac.ir/article_2185_a045a2ddcb34f2ca54fb1b94b03a2d26.pdf
Population mean
sample size determination
two phase sampling