J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 Research Paper \$4\$-total mean cordial labeling in subdivision graphs Ponraj R Department of Mathematics Sri Parakalyani College Alwarkurichi -627 412, India SUBBULAKSHMI S Sri Paramakalyani College Alwarkurichi-627412, Tamilnadu, India Somasundaram S Department of Mathematics Manonmaniam sundarnar university, Abishekapatti, Tirunelveli-627012, Tamilnadu, India 01 12 2020 52 2 1 11 21 11 2020 21 11 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_78640.html

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.

corona subdivision of star subdivision of bistar subdivision of comb subdivision of crown subdivision of double comb subdivision of ladder
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 Research Paper Linear optimization constrained by fuzzy inequalities defined by Max-Min averaging operator Ghodousian A. University of Tehran, College of Engineering, Faculty of Engineering Science Falahatkar Sara University of Tehran, College of Engineering, Faculty of Engineering Science 01 12 2020 52 2 13 28 20 12 2020 20 12 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79080.html

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.

Fuzzy relation fuzzy relational inequality Linear programming fuzzy compositions and fuzzy averaging operator graph
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 Research Paper Crypto- Currency Price Prediction with Decision Tree Based Regressions Approach naghib moayed ali Department of Statistics, Allameh Tabatabyee University Habibi Reza Iran Banking Institute, Central Bank of Iran 01 12 2020 52 2 29 40 22 12 2020 22 12 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79110.html

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).

Crypto currency price prediction Decision Tree ARIMA
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 Research Paper Implementation of Combinational Logic Circuits Using Nearest-Neighbor One-Dimensional Four-State Cellular Automata Javan Abolfazl University of Tehran, College of Engineering, Faculty of Engineerng Science, Department of Algorithms and Computation Jafarpour Maryam Department of Algorithms and Computation, College of Engineering, University of Tehran Tehran, 1417613131, Iran Moieni Ali University of Tehran, College of Engineering, Faculty of Engineerng Science, Department of Algorithms and Computation Shekaramiz Mohammad Department of Electrical and Computer Engineering, Utah State University Logan, UT 84322-4120, USA 01 12 2020 52 2 41 56 28 12 2020 28 12 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79225.html

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.

cellular automata Cellular Machine Combinational Logic Circuits universality
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 unavailable On the domination number of generalized Petersen graphs Poureidi Abolfazl Department of Mathematics, Shahrood University of Technology Shahrood, Iran 01 12 2020 52 2 57 65 28 12 2020 28 12 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79236.html

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)\$.

Dominating set Algorithm Dynamic Programming Generalized Petersen graph
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 Research Paper On Hardy's Apology Numbers Koppelaar Dr. Henk Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The NetherlandsVredenburchstede 20 Nasehpour Peyman Department of Engineering Science \\ Golpayegan University of Technology 01 12 2020 52 2 67 83 29 12 2020 29 12 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79248.html

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.

Hardy's apology numbers Armstrong numbers Dudeney numbers Wells numbers
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 Research Paper LP Problems on the max - “Fuzzy Or” inequalities systems Ghodousian A. University of Tehran, College of Engineering, Faculty of Engineering Science Mirhashemi Parmida University of Tehran, College of Engineering, Faculty of Engineering Science, 01 12 2020 52 2 85 98 29 12 2020 29 12 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79249.html

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.

Fuzzy relation fuzzy relational inequality linear optimization fuzzy compositions and fuzzy averaging operator
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 unavailable Generalization of DP Curves and Surfaces Bakhshesh Davood Department of Computer Science, University of Bojnord, Bojnord, Iran. 01 12 2020 52 2 99 108 31 12 2020 31 12 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79264.html

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.

B\'{e}zier curve DP curve CAGD
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 Research Paper On the optimization of Hadoop MapReduce default job scheduling through dynamic job prioritization Peyravi Narges Department of Computer Engineering and Information Technology, Faculty of Engineering, University of Qom, Qom, Iran Moeini Ali Department of Algorithms and Computation, School of Engineering Science, College of Engineering, University of Tehran 01 12 2020 52 2 109 126 31 12 2020 31 12 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79266.html

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.

Hadoop MapReduce Job scheduling Prioritization dynamic priority score
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 Research Paper Fuzzy Cumulative Distribution Function and its Properties Shams Mehdi Department of Mathematical Sciences, University of Kashan, Isfahan, Iran. Hesamian Gholamreza Department of Statistics, Payame Noor University, Tehran 19395-3697, Iran 01 12 2020 52 2 127 136 31 12 2020 31 12 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79267.html

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.

Cumulative Distribution Function Fuzzy random variable fuzzy parameter ranking method convergence divergence to infinity
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 Research Paper Two different inverse eigenvalue problems for nonsymmetric tridiagonal matrices Fathi Ferya Department of Mathematics, Central Tehran Branch, Islamic Azad University, Tehran, Iran Fariborzi Araghi Mohammad Ali Department of Mathematics, Faculty of Sciences, Central Tehran branch, Islamic Azad university, Tehran, Iran. Shahzadeh Fazeli Seyed Abolfazl Department of Computer Science, Yazd University, Yazd, Iran. 01 12 2020 52 2 137 148 31 12 2020 31 12 2020 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79269.html

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.

Inverse eigenvalue problem Tridiagonal matrix Principal submatrix
J. Algorithm Comput. University of Tehran Journal of Algorithms and Computation 2476-2776 University of Tehran 129 Research Paper A note on the approximability of the tenacity of graphs Heidari Vahid University of Tehran, Department of Algorithms and Computation. Moazzami Dara University of Tehran, College of Engineering, Faculty of Engineering Science 01 12 2020 52 2 149 157 01 01 2021 01 01 2021 Copyright © 2020, University of Tehran. 2020 https://jac.ut.ac.ir/article_79270.html

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}\$.

\$NP\$-complete problem Tenacity Tenacious \$NP\$-hard