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