University of TehranJournal of Algorithms and Computation2476-277652220201201$4$-total mean cordial labeling in subdivision graphs11178640ENRPonrajDepartment of Mathematics
Sri Parakalyani College
Alwarkurichi -627 412, IndiaSSUBBULAKSHMISri Paramakalyani College
Alwarkurichi-627412, Tamilnadu, IndiaSSomasundaramDepartment of Mathematics
Manonmaniam sundarnar university, Abishekapatti, Tirunelveli-627012,
Tamilnadu, IndiaJournal Article20201121Let $G$ 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.https://jac.ut.ac.ir/article_78640_417b0db101ba534580bcc1065d70cdd3.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201Linear optimization constrained by fuzzy inequalities defined by Max-Min averaging operator132879080ENA.GhodousianUniversity of Tehran, College of Engineering, Faculty of Engineering Science0000-0002-9224-8470SaraFalahatkarUniversity of Tehran, College of Engineering, Faculty of Engineering ScienceJournal Article20201220In 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.https://jac.ut.ac.ir/article_79080_dbd6cabd14838434f023bf778552f3e4.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201Crypto- Currency Price Prediction with Decision Tree Based Regressions Approach294079110ENAliNaghib MoayedDepartment of Statistics, Allameh Tabatabyee UniversityRezaHabibiIran Banking Institute, Central Bank of IranJournal Article20201222Generally, 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.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201Implementation of Combinational Logic Circuits Using Nearest-Neighbor One-Dimensional Four-State Cellular Automata415679225ENAbolfazlJavanUniversity of Tehran, College of Engineering, Faculty of Engineerng Science, Department of Algorithms and ComputationMaryamJafarpourDepartment of Algorithms and Computation, College of Engineering, University of Tehran Tehran, 1417613131, Iran0000-0001-7266-5018AliMoieniUniversity of Tehran, College of Engineering, Faculty of Engineerng Science, Department of Algorithms and ComputationMohammadShekaramizDepartment of Electrical and Computer Engineering,
Utah State University
Logan, UT 84322-4120, USAJournal Article20201228Cellular 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.<br />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.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201On the domination number of generalized Petersen graphs576579236ENAbolfazlPoureidiDepartment of Mathematics, Shahrood University of Technology Shahrood, IranJournal Article20201228Let $n$ and $k$ be integers such that $3leq 2k+ 1 leq n$.<br />The generalized Petersen graph $GP(n, k)=(V,E) $ is the graph with <br />$V={u_1, u_2,ldots, u_n}cup{v_1, v_2,ldots, v_n}$ and $E={u_iu_{i+1}, u_iv_i, v_iv_{i+k}: 1 leq i leq n}$, where<br />addition 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 $k=mathcal{O}(1)$.https://jac.ut.ac.ir/article_79236_83169ff58aaf301dce65ecd29d8d6030.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201On Hardy's Apology Numbers678379248ENDr. HenkKoppelaarFaculty of Electrical Engineering, Mathematics and Computer Science,
Delft University of Technology,
Delft,
The NetherlandsVredenburchstede 200000-0001-7487-6564PeymanNasehpourDepartment of Engineering Science \\
Golpayegan University of TechnologyJournal Article20201229Twelve 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.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201LP Problems on the max - “Fuzzy Or” inequalities systems859879249ENA.GhodousianUniversity of Tehran, College of Engineering, Faculty of Engineering Science0000-0002-9224-8470ParmidaMirhashemiUniversity of Tehran, College of Engineering, Faculty of Engineering Science,0000-0001-6326-0449Journal Article20201229In 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.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201Generalization of DP Curves and Surfaces9910879264ENDavoodBakhsheshDepartment of Computer Science, University of Bojnord, Bojnord, Iran.Journal Article20201231In 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.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201On the optimization of Hadoop MapReduce default job scheduling through dynamic job prioritization10912679266ENNargesPeyraviDepartment of Computer Engineering and Information Technology, Faculty of Engineering, University of Qom, Qom, IranAliMoeiniDepartment of Algorithms and Computation, School of Engineering Science, College of Engineering, University of TehranJournal Article20201231One 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.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201Fuzzy Cumulative Distribution Function and its Properties12713679267ENMehdiShamsDepartment of Mathematical Sciences, University of Kashan, Isfahan, Iran.GholamrezaHesamianDepartment of Statistics, Payame Noor University, Tehran 19395-3697, IranJournal Article20201231The 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.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201Two different inverse eigenvalue problems for nonsymmetric tridiagonal matrices13714879269ENFeryaFathiDepartment of Mathematics, Central Tehran Branch, Islamic Azad University, Tehran,
IranMohammad AliFariborzi AraghiDepartment of Mathematics, Faculty of Sciences, Central Tehran branch, Islamic Azad university, Tehran, Iran.0000-0002-5467-9296Seyed AbolfazlShahzadeh FazeliDepartment of Computer Science, Yazd University, Yazd, Iran.0000-0002-3724-8689Journal Article20201231Inverse 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.<br />The algorithms and numerical examples are given to show the applicability of the proposed scheme.https://jac.ut.ac.ir/article_79269_ecc0d219b5c8c3f9e1df951b33d76cdb.pdfUniversity of TehranJournal of Algorithms and Computation2476-277652220201201A note on the approximability of the tenacity of graphs14915779270ENVahidHeidariUniversity of Tehran, Department of Algorithms and Computation.DaraMoazzamiUniversity of Tehran, College of Engineering, Faculty of Engineering ScienceJournal Article20210101In this paper we show that, if $NPneq ZPP$, for any $epsilon > 0$, the tenacity of graph<br />with $n$ vertices is not approximable in polynomial time within a factor of<br />$frac{1}{2} left( frac{n-1}{2} right) ^{1-epsilon}$.https://jac.ut.ac.ir/article_79270_0a4d1e9aa72c099beb4fcfe521d1bc23.pdf