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International Journal of Computing Science and Applied Mathematics

ijcsam
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Published by Institut Teknologi Sepuluh Nopember Surabaya

ISSN : - EISSN : 24775401 DOI : -

Core Subject : Science, Education,

Computer Science & IT Education Mathematics

(IJCSAM) International Journal of Computing Science and Applied Mathematics is an open access journal publishing advanced results in the fields of computations, science and applied mathematics, as mentioned explicitly in the scope of the journal. The journal is geared towards dissemination of original research and practical contributions by both scientists and engineers, from both academia and industry.

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Articles 7 Documents

Search results for , issue "Vol 3, No 1 (2017)" : 7 Documents clear

State Variable Estimation of Nonisothermal Continuous Stirred Tank Reactor Using Fuzzy Kalman Filter Risa Fitria; Didik Khusnul Arif
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 3, No 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Increasing safety and product quality, reducing manufacturing cost, minimizing the impact of environment in fault detection system for Nonisothermal Continuous Stirred Tank Reactor (CSTR) are the reason why accurate state estimation is needed. Kalman filter is an estimation algorithm of the stochastic linear dynamical system. Through this work, a modification of Kalman Filter that combines with fuzzy theory, namely Fuzzy Kalman Filter (FKF) is presented to estimate the state variable of Non-Isothermal CSTR. First, we approximate the nonlinear system of CSTR as piecewise linear functions and then change the crisp variable into the fuzzy form. The estimation results are simulated using Matlab. The simulation shows the comparison results, i.e computational time and accuracy, between FKF and Ensemble Kalman Filter (EnKF). The final result of these case shows that FKF is better than EnKF to estimate the state variable of Nonisothermal CSTR. The error estimation of FKF is 72.9% smaller for estimation of reactans concentration, 39.9% smaller for tank temperature, 76.47% smaller for cooling jacket temperature and the computational time of FKF is 76.47% faster than the computational time of EnKF.

Speed Estimation On Moving Vehicle Based On Digital Image Processing Danang Wahyu Wicaksono; Budi Setiyono
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 3, No 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Along with the development of information and communication technology, the world urban people now recognize a new term called Smart City. One of Smart City components is smart transportation, known as Intelligent Transportation System (ITS) in which there is transportation management on the highway. Installation of CCTV (Closed Circuit Television) on the streets are now widely performed. It can be used to monitor conditions and detect problems such as traffic jam and vehicle speed limit violation. This research focuses on vehicle speed estimation using image processing from video data and Euclidean distance method with many different camera angles. The first step, video data is extracted into frames and applied preprocessing to extracted frames to minimize shadow effect. Then, using Gaussian Mixture Model (GMM) to extract foreground image. In the next step, the obtained foreground is filtered using median filter, shadow removing, and morphology operation. The detected vehicle object will be tracked to determine the location in each frame to estimate the speed based on its distance between frames. From the obtained results, this system is capable on estimating the speed of moving vehicle with the lowest accuracy is 87.01% and the highest accuracy is 99.38%.

The Fuzzy Lattice of Ideals and Filters of an Almost Distributive Fuzzy Lattice Berhanu Assaye Alaba; Bekalu Tarekegn Bitew
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 3, No 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

In this paper, the concept of fuzzy lattice is discussed. It is proved that a fuzzy poset (IA(L),B) and (FA(L),B) forms a fuzzy lattice, where IA(L) and FA(L) are the set containing all ideals, and the set containing all filters of an Almost Distributive Fuzzy Lattice(ADFL) respectively. In addition we proved that, a fuzzy poset (PIA(L),B) and (PFA(L),B) forms fuzzy distributive lattice, where PIA and PFA(L) denotes the set containing all principal ideals and the set containing all principal filters of an ADFL. Finally, it is proved that for any ideal I and filter F of an ADFL, IiA = {(i]A : i in I} and FfA = {[f)A : f in F} are ideals of a fuzzy distributive lattice (PIA(L),B) and (PFA(L),B) respectively, and FiA = {(f]A : f in F} and IfA = {[i)A : i in I} are filters of a distributive fuzzy lattice (PIA(L),B) and (PFA(L),B) respectively.

Sequence Alignment Using Nature-Inspired Metaheuristic Algorithms Muhammad Luthfi Shahab; Mohammad Isa Irawan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 3, No 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

The most basic process in sequence analysis is sequence alignment, usually solved by dynamic programming Needleman-Wunsch algorithm. However, Needleman-Wunsch algorithm has some lack when the length of the sequence which is aligned is big enough. Because of that, sequence alignment is solved by metaheuristic algorithms. In the present, there are a lot of new metaheuristic algorithms based on natural behavior of some species, we usually call them as nature-inspired metaheuristic algorithms. Some of those algorithm that are more efficient are firefly algorithm, cuckoo search, and flower pollination algorithm. In this research, we use those algorithms to solve sequence alignment. The results show that those algorithms can be used to solve sequence alignment with good result and linear time computation.

Second Degree Refinement Jacobi Iteration Method for Solving System of Linear Equation Tesfaye Kebede
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 3, No 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Several iterative techniques for the solution of linear system of equations have been proposed in different literature in the past.In this paper, we present a Second degree of refinement Jacobi Iteration method for solving system of linear equation, Ax = b and we consider few numerical examples and spectral radius to show that the effective of the Second degree of refinement Jacobi Iteration Method (SDRJ) in comparison with other methods of First degree Jacobi (FDJ), First degree Refinement Jacobi (FDRJ) and Second degree Jacobi (SDJ) method.

Object Oriented Design of Software Tool for Finite Abstractions of Max-Plus-Linear Systems using Unified Modeling Language Muhammadun Muhammadun; Dieky Adzkiya; Imam Mukhlash
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 3, No 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Max-Plus-Linear (MPL) systems are a class of discrete-event systems with a continuous state space characterizing the timing of the underlying sequential discrete events. There is a formal approach to analyze these systems based on finite abstractions. The abstraction algorithms have been in MATLAB using list data structure and in JAVA using tree data structure. The MATLAB implementation requires long computational time, whereas the JAVA one requires larger memory allocation. In this work, we discuss an object oriented design in C++ using tree data structure without recursive functions in the hope of improving the results obtained by the two previous implementations.

A Study on Parthenogenesis of Petersen Graph Amiroch, Siti; Kiratama, Danang
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 3, No 1 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Genetics is the science of trait from the parent to the descendant. In biology, genetics pass a series of genes unification process that takes place in the chromosome. The results of genes unification will form the nature and character of the generation. This particular genetic process also applies in graph theory. Genetics on graph theory is divided into two: breeding and parthenogenesis. This present study elaborated a single type of genetic processes that was parthenogenesis which is applied on a Petersen graph. Through the similar process to genetics in biology, Petersen graph will be reconstructed and combined with other graphs (gene) in purposes to create a descendant or a new graph with new nature and characteristic. Based on the result of parthenogenesis on this Petersen graph, there was derived a graph which has 18 edges and 12 vertices, isomorphism toward another Petersen graph, Hamiltonian, and has 3 girth and symmetric.

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