ORIGINAL_ARTICLE
$4$-total mean cordial labeling in subdivision graphs
Let $G$ be a graph. Let $f:V\left(G\right)\rightarrow \left\{0,1,2,\ldots,k-1\right\}$ be a function where $k\in \mathbb{N}$ and $k>1$. For each edge $uv$, assign the label $f\left(uv\right)=\left\lceil \frac{f\left(u\right)+f\left(v\right)}{2}\right\rceil$. $f$ is called $k$-total mean cordial labeling of $G$ if $\left|t_{mf}\left(i\right)-t_{mf}\left(j\right) \right| \leq 1$, for all $i,j\in\left\{0,1,2,\ldots,k-1\right\}$, where $t_{mf}\left(x\right)$ denotes the total number of vertices and edges labelled with $x$, $x\in\left\{0,1,2,\ldots,k-1\right\}$. A graph with admit a $k$-total mean cordial labeling is called $k$-total mean cordial graph.
https://jac.ut.ac.ir/article_78640_417b0db101ba534580bcc1065d70cdd3.pdf
2020-12-01
1
11
corona
subdivision of star
subdivision of bistar
subdivision of comb
subdivision of crown
subdivision of double comb
subdivision of ladder
R
Ponraj
ponrajmaths@gmail.com
1
Department of Mathematics Sri Parakalyani College Alwarkurichi -627 412, India
LEAD_AUTHOR
S
SUBBULAKSHMI
ssubbulakshmis@gmail.com
2
Sri Paramakalyani College Alwarkurichi-627412, Tamilnadu, India
AUTHOR
S
Somasundaram
somutvl@gmail.com
3
Department of Mathematics Manonmaniam sundarnar university, Abishekapatti, Tirunelveli-627012, Tamilnadu, India
AUTHOR
ORIGINAL_ARTICLE
Linear optimization constrained by fuzzy inequalities defined by Max-Min averaging operator
In this paper, optimization of a linear objective function with fuzzy relational inequality constraints is investigated whereby the feasible region is formed as the intersection of two inequality fuzzy systems and \textquotedblleft Fuzzy Max-Min\textquotedblright \ averaging operator is considered as fuzzy composition. It is shown that a lower bound is always attainable for the optimal objective value. Also, it is proved that the optimal solution of the problem is always resulted from the unique maximum solution and a minimal solution of the feasible region. An algorithm is presented to solve the problem and an example is described to illustrate the algorithm.
https://jac.ut.ac.ir/article_79080_dbd6cabd14838434f023bf778552f3e4.pdf
2020-12-01
13
28
Fuzzy relation
fuzzy relational inequality
Linear programming
fuzzy compositions and fuzzy averaging operator graph
A.
Ghodousian
a.ghodousian@ut.ac.ir
1
University of Tehran, College of Engineering, Faculty of Engineering Science
LEAD_AUTHOR
Sara
Falahatkar
sara.falahat@ut.ac.ir
2
University of Tehran, College of Engineering, Faculty of Engineering Science
AUTHOR
ORIGINAL_ARTICLE
Crypto- Currency Price Prediction with Decision Tree Based Regressions Approach
Generally, no one can reject the fact that crypto currency market is expanded rapidly during last few years as, nowadays, crypto currency market is attractive for both traders and business who are not willing to pay for FATF services for transferring money. With this in mind, crypto currency price prediction is crucial for many people and business entities. While there have been quite a few conventional statistical models to forecast crypto currency prices, we decided to make price prediction using decision Tree Based Regression. In this research we devised a decision tree models to predict Bitcoin which is the most renowned and frequently used crypto currency. we used Volume from, Volume to, New addresses, Active addresses, large transaction count, Block height, Hash rate, Difficulty, Current supply as predictor variables in addition to historical crypto currency price data during the with a total of 1000 Observations. We find that forecasting accuracy of decision tree models are higher than benchmark models such as linear regression and autoregressive integrated moving average(ARIMA).
https://jac.ut.ac.ir/article_79110_6156628d39397c2b78824976d69d9b12.pdf
2020-12-01
29
40
Crypto currency price prediction
Decision Tree
ARIMA
ali
naghib moayed
ali.ampmk@gmail.com
1
Department of Statistics, Allameh Tabatabyee University
AUTHOR
Reza
Habibi
r_habibi@ibi.ac.ir
2
Iran Banking Institute, Central Bank of Iran
LEAD_AUTHOR
ORIGINAL_ARTICLE
Implementation of Combinational Logic Circuits Using Nearest-Neighbor One-Dimensional Four-State Cellular Automata
Cellular automata are simple mathematical idealizations of natural systems. They consist of a lattice of discrete identical sites, each site taking on a finite set of, say, integer values. Over the years, scientists have been trying to investigate the computational capabilities of cellular automata by limiting the dimension, neighborhood radius, and the number of states.In this article, we represent a novel implementation of combinational logic circuits using nearest-neighbor one-dimensional four-state cellular automata (CA). The novelty behind the proposed model is the reduction of the required number of states and yet being able to implement combinational logic-circuits in the conventional CA fashion. This can open a new window to the computation using cellular automata.
https://jac.ut.ac.ir/article_79225_bb5fb4256d7b683d0530681b354a0cb1.pdf
2020-12-01
41
56
cellular automata
Cellular Machine
Combinational Logic Circuits
universality
Abolfazl
Javan
ajavan@ut.ac.ir
1
University of Tehran, College of Engineering, Faculty of Engineerng Science, Department of Algorithms and Computation
AUTHOR
Maryam
Jafarpour
m.jafarpour@ut.ac.ir
2
Department of Algorithms and Computation, College of Engineering, University of Tehran Tehran, 1417613131, Iran
LEAD_AUTHOR
Ali
Moieni
moeini@ut.ac.ir
3
University of Tehran, College of Engineering, Faculty of Engineerng Science, Department of Algorithms and Computation
AUTHOR
Mohammad
Shekaramiz
mohammad.shekaramiz@aggiemail.usu.edu
4
Department of Electrical and Computer Engineering, Utah State University Logan, UT 84322-4120, USA
AUTHOR
ORIGINAL_ARTICLE
On the domination number of generalized Petersen graphs
Let $n$ and $k$ be integers such that $3\leq 2k+ 1 \leq n$.The generalized Petersen graph $GP(n, k)=(V,E) $ is the graph with $V=\{u_1, u_2,\ldots, u_n\}\cup\{v_1, v_2,\ldots, v_n\}$ and $E=\{u_iu_{i+1}, u_iv_i, v_iv_{i+k}: 1 \leq i \leq n\}$, whereaddition is in modulo $n$. A subset $D\subseteq V$ is a dominating set of $GP(n, k)$ if for each $v\in V\setminus D$ there is a vertex $u\in D$ adjacent to $v$. The minimum cardinality of a dominating set of $GP(n, k)$ is called the domination number of $GP(n, k)$.
In this paper we give a dynamic programming algorithm for computing the domination number of a given $GP(n,k )$ in $\mathcal{O}(n)$ time and space for every $k=\mathcal{O}(1)$.
https://jac.ut.ac.ir/article_79236_83169ff58aaf301dce65ecd29d8d6030.pdf
2020-12-01
57
65
Dominating set
Algorithm
Dynamic Programming
Generalized Petersen graph
Abolfazl
Poureidi
a.poureidi@shahroodut.ac.ir
1
Department of Mathematics, Shahrood University of Technology Shahrood, Iran
LEAD_AUTHOR
ORIGINAL_ARTICLE
On Hardy's Apology Numbers
Twelve well known `Recreational' numbers are generalized and classified in three generalized types Hardy, Dudeney, and Wells. A novel proof method to limit the search for the numbers is exemplified for each of the types. Combinatorial operators are defined to ease programming the search.
https://jac.ut.ac.ir/article_79248_56d3c030088a170a3906b627fcde5388.pdf
2020-12-01
67
83
Hardy's apology numbers
Armstrong numbers
Dudeney numbers
Wells numbers
Dr.
Koppelaar
koppelaar.henk@gmail.com
1
Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The NetherlandsVredenburchstede 20
AUTHOR
Peyman
Nasehpour
nasehpour@gut.ac.ir
2
Department of Engineering Science \\ Golpayegan University of Technology
LEAD_AUTHOR
ORIGINAL_ARTICLE
LP Problems on the max - “Fuzzy Or” inequalities systems
In this paper, optimization of a linear objective function with fuzzy relational inequality constraints is investigated whereby the feasible region is formed as the intersection of two inequality fuzzy systems and “Fuzzy Or” operator is considered as fuzzy composition. It is shown that a lower bound is always attainable for the optimal objective value. Also, it is proved that the optimal solution of the problem is always resulted from the unique maximum solution and a minimal solution of the feasible region. An algorithm is presented to solve the problem and an example is described to illustrate the algorithm.
https://jac.ut.ac.ir/article_79249_c198efc6bb40dcd88841addc34b6ec2c.pdf
2020-12-01
85
98
Fuzzy relation
fuzzy relational inequality
linear optimization
fuzzy compositions and fuzzy averaging operator
A.
Ghodousian
a.ghodousian@ut.ac.ir
1
University of Tehran, College of Engineering, Faculty of Engineering Science
LEAD_AUTHOR
Parmida
Mirhashemi
par.mirhashemi@ut.ac.ir
2
University of Tehran, College of Engineering, Faculty of Engineering Science,
AUTHOR
ORIGINAL_ARTICLE
Generalization of DP Curves and Surfaces
In CAGD, the DP curves are known as a normalized totally positive curves that have the linear computational complexity. Because of their geometric properties, these curves will have the shape preserving properties, that is, the form of the curve will maintain the shape of the polygon and optimal stability. In this paper, we first define a new basis functions that are called generalized DP basis functions. Based on these functions, the generalized DP curves and surfaced are defined which have most properties of the classical DP curves and surfaces. These curves and surfaces have geometric properties as the rational DP curves and surfaces. Furthermore, we show that the shape parameters can control the shape of the proposed curve without changing the control points.
https://jac.ut.ac.ir/article_79264_7b24762116d5b5830b5d4ad475da353f.pdf
2020-12-01
99
108
B'{e}zier curve
DP curve
CAGD
Davood
Bakhshesh
d.bakhshesh@ub.ac.ir
1
Department of Computer Science, University of Bojnord, Bojnord, Iran.
LEAD_AUTHOR
ORIGINAL_ARTICLE
On the optimization of Hadoop MapReduce default job scheduling through dynamic job prioritization
One of the most popular frameworks for big data processing is Apache Hadoop MapReduce. The default Hadoop scheduler uses queue system. However, it does not consider any specific priority for the jobs required for MapReduce programming model. In this paper, a new dynamic score is developed to improve the performance of the default Hadoop MapReduce scheduler. This dynamic priority score is computed based on effective factors such as job runtime estimation, input data size, waiting time, and length or bustle of the waiting queue. The implementation of the proposed scheduling method, based on this dynamic score, not only improves CPU and memory performance, but also reduced waiting time and average turnaround time by approximately $45\%$ and $40\%$ respectively, compared to the default Hadoop scheduler.
https://jac.ut.ac.ir/article_79266_1ccbac12d443ad1cb51ac9305190b1b3.pdf
2020-12-01
109
126
Hadoop MapReduce
Job scheduling
Prioritization
dynamic priority score
Narges
Peyravi
narges.peyravi@gmail.com
1
Department of Computer Engineering and Information Technology, Faculty of Engineering, University of Qom, Qom, Iran
AUTHOR
Ali
Moeini
moeini@ut.ac.ir
2
Department of Algorithms and Computation, School of Engineering Science, College of Engineering, University of Tehran
LEAD_AUTHOR
ORIGINAL_ARTICLE
Fuzzy Cumulative Distribution Function and its Properties
The statistical methods based on cumulative distribution function is a start point for many parametric or nonparametric statistical inferences. However, there are many practical problems that require dealing with observations/parameters that represent inherently imprecise. However, Hesamian and Taheri (2013) was extended a concept of fuzzy cumulative distribution function. Applying a common notion of fuzzy random variables, they extended a vague concept of fuzzy cumulative distribution function. However, the main properties of the proposed method has not yet been considered in fuzzy environment. This paper aims to extend the classical properties of the fuzzy cumulative distribution function in fuzzy environment.
https://jac.ut.ac.ir/article_79267_82f43625d638278d11153074cd36964c.pdf
2020-12-01
127
136
Cumulative Distribution Function
Fuzzy random variable
fuzzy parameter
ranking method
convergence
divergence to infinity
Mehdi
Shams
mehdishams@kashanu.ac.ir
1
Department of Mathematical Sciences, University of Kashan, Isfahan, Iran.
LEAD_AUTHOR
Gholamreza
Hesamian
gh.hesamian@pnu.ac.ir
2
Department of Statistics, Payame Noor University, Tehran 19395-3697, Iran
AUTHOR
ORIGINAL_ARTICLE
Two different inverse eigenvalue problems for nonsymmetric tridiagonal matrices
Inverse eigenvalue problems (IEPs) of tridiagonal matrices are among the most popular IEPs, this is due to the widespread application of this matrix. In this paper, two different IEPs with different eigen information including eigenvalues and eigenvectors are presented on the nonsymmetric tridiagonal matrix. A recursive relation of characteristic polynomials of the leading principal submatrices of the required matrix is presented to solve the problems. The application of the problems in graph and perturbation theory is studied. The necessary and sufficient conditions for solvability of the problems are obtained.The algorithms and numerical examples are given to show the applicability of the proposed scheme.
https://jac.ut.ac.ir/article_79269_ecc0d219b5c8c3f9e1df951b33d76cdb.pdf
2020-12-01
137
148
Inverse eigenvalue problem
Tridiagonal matrix
Principal submatrix
Ferya
Fathi
ferya.fathi@gmail.com
1
Department of Mathematics, Central Tehran Branch, Islamic Azad University, Tehran, Iran
AUTHOR
Mohammad Ali
Fariborzi Araghi
fariborzi.araghi@gmail.com
2
Department of Mathematics, Faculty of Sciences, Central Tehran branch, Islamic Azad university, Tehran, Iran.
LEAD_AUTHOR
Seyed Abolfazl
Shahzadeh Fazeli
fazeli@yazd.ac.ir
3
Department of Computer Science, Yazd University, Yazd, Iran.
AUTHOR
ORIGINAL_ARTICLE
A note on the approximability of the tenacity of graphs
In this paper we show that, if $NP\neq ZPP$, for any $\epsilon > 0$, the tenacity of graphwith $n$ vertices is not approximable in polynomial time within a factor of$\frac{1}{2} \left( \frac{n-1}{2} \right) ^{1-\epsilon}$.
https://jac.ut.ac.ir/article_79270_0a4d1e9aa72c099beb4fcfe521d1bc23.pdf
2020-12-01
149
157
$NP$-complete problem
Tenacity
Tenacious
$NP$-hard
Vahid
Heidari
vahid.heidari@ut.ac.ir
1
University of Tehran, Department of Algorithms and Computation.
AUTHOR
Dara
Moazzami
dmoazzami@ut.ac.ir
2
University of Tehran, College of Engineering, Faculty of Engineering Science
LEAD_AUTHOR