فهرست مطالب

  • Volume:52 Issue: 2, Dec 2020
  • تاریخ انتشار: 1399/11/27
  • تعداد عناوین: 12
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  • R. Ponraj *, S. SUBBULAKSHMI, S .Somasundaram Pages 1-11

    Let $G$ be a graph. Let $f:Vleft(Gright)rightarrow left{0,1,2,ldots,k-1right}$ be a function where $kin mathbb{N}$ and $k>1$. For each edge $uv$, assign the label $fleft(uvright)=leftlceil frac{fleft(uright)+fleft(vright)}{2}rightrceil$.  $f$ is called $k$-total mean cordial labeling of $G$ if $left|t_{mf}left(iright)-t_{mf}left(jright) right| leq 1$, for all $i,jinleft{0,1,2,ldots,k-1right}$, where $t_{mf}left(xright)$ denotes the total number of vertices and edges labelled with $x$, $xinleft{0,1,2,ldots,k-1right}$.  A graph with admit a $k$-total mean cordial labeling is called $k$-total mean cordial graph.

    Keywords: corona, subdivision of star, subdivision of bistar, subdivision of comb, subdivision of crown, subdivision of double comb, subdivision of ladder
  • A. Ghodousian *, Sara Falahatkar Pages 13-28
    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-Mintextquotedblright 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.
    Keywords: Fuzzy relation, fuzzy relational inequality, Linear programming, fuzzy compositions, fuzzy averaging operator graph
  • Ali Naghib Moayed, Reza Habibi * Pages 29-40
    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).
    Keywords: Crypto currency price prediction, Decision Tree, ARIMA
  • Abolfazl Javan, Maryam Jafarpour *, Ali Moieni, Mohammad Shekaramiz Pages 41-56
    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.
    Keywords: cellular automata, Cellular Machine, Combinational Logic Circuits, universality
  • Abolfazl Poureidi * Pages 57-65
    Let $n$ and $k$ be integers such that $3leq 2k+ 1 leq n$.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 $Dsubseteq V$ is a dominating set of $GP(n, k)$ if for each $vin Vsetminus D$ there is a vertex $uin D$ 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 $k=mathcal{O}(1)$.
    Keywords: Dominating set, Algorithm, Dynamic Programming, Generalized Petersen graph
  • Peyman Nasehpour *, Henk Koppelaar Pages 67-83

    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.

    Keywords: Hardy's apology numbers, Armstrong numbers, Dudeney numbers, Wells numbers
  • A. Ghodousian *, Parmida Mirhashemi Pages 85-98
    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.
    Keywords: Fuzzy relation, fuzzy relational inequality, linear optimization, fuzzy compositions, fuzzy averaging operator
  • Davood Bakhshesh * Pages 99-108
    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.
    Keywords: B'{e}zier curve, DP curve, CAGD
  • Narges Peyravi, Ali Moeini * Pages 109-126
    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.
    Keywords: Hadoop MapReduce, Job scheduling, Prioritization, dynamic priority score
  • Mehdi Shams *, Gholamreza Hesamian Pages 127-136
    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.
    Keywords: Cumulative Distribution Function, Fuzzy random variable, fuzzy parameter, ranking method, convergence, divergence to infinity
  • Ferya Fathi, MohammadAli Fariborzi Araghi *, Seyed Abolfazl Shahzadeh Fazeli Pages 137-148

    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.

    Keywords: Inverse eigenvalue problem, Tridiagonal matrix, Principal submatrix
  • Vahid Heidari, Dara Moazzami * Pages 149-157
    In this paper we show that, if $NPneq ZPP$, for any $epsilon > 0$, the tenacity of graphwith $n$ vertices is not approximable in polynomial time within a factor of$frac{1}{2} left( frac{n-1}{2} right) ^{1-epsilon}$.
    Keywords: $NP$-complete problem, Tenacity, Tenacious, $NP$-hard