Journals / CMES / online First
Table of Content


  • Research Article

    Deep-Learning-Based Production Decline Curve Analysis in the Gas Reservoir through Sequence Learning Models

    Shaohua Gu1,2, Jiabao Wang3, Liang Xue3,*, Bin Tu3, Mingjin Yang3, Yuetian Liu3
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.019435
    (This article belongs to this Special Issue: Modeling of Fluids Flow in Unconventional Reservoirs)
    Abstract Production performance prediction of tight gas reservoirs is crucial to the estimation of ultimate recovery, which has an important impact on gas field development planning and economic evaluation. Owing to the model’s simplicity, the decline curve analysis method has been widely used to predict production performance. The advancement of deep-learning methods provides an intelligent way of analyzing production performance in tight gas reservoirs. In this paper, a sequence learning method to improve the accuracy and efficiency of tight gas production forecasting is proposed. The sequence learning methods used in production performance analysis herein include the recurrent neural network (RNN), long… More >

  • Research Article

    Strategy for Creating AR Applications in Static and Dynamic Environments Using SLAM- and Marker Detector-Based Tracking

    Chanho Park1,2, Hyunwoo Cho1, Sangheon Park1, Sung-Uk Jung1, Suwon Lee3,*
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.019214
    (This article belongs to this Special Issue: Algebra, Number Theory, Combinatorics and Their Applications: Mathematical Theory and Computational Modelling)
    Abstract Recently, simultaneous localization and mapping (SLAM) has received considerable attention in augmented reality (AR) libraries and applications. Although the assumption of scene rigidity is common in most visual SLAMs, this assumption limits the possibilities of AR applications in various real-world environments. In this paper, we propose a new tracking system that integrates SLAM with a marker detection module for real-time AR applications in static and dynamic environments. Because the proposed system assumes that the marker is movable, SLAM performs tracking and mapping of the static scene except for the marker, and the marker detector estimates the 3-dimensional pose of the… More >

  • Research Article

    An Improved Gorilla Troops Optimizer Based on Lens Opposition-Based Learning and Adaptive β-Hill Climbing for Global Optimization

    Yaning Xiao, Xue Sun*, Yanling Guo, Sanping Li, Yapeng Zhang, Yangwei Wang
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.019198
    (This article belongs to this Special Issue: Swarm Intelligence and Applications in Combinatorial Optimization)
    Abstract Gorilla troops optimizer (GTO) is a newly developed meta-heuristic algorithm, which is inspired by the collective lifestyle and social intelligence of gorillas. Similar to other metaheuristics, the convergence accuracy and stability of GTO will deteriorate when the optimization problems to be solved become more complex and flexible. To overcome these defects and achieve better performance, this paper proposes an improved gorilla troops optimizer (IGTO). First, Circle chaotic mapping is introduced to initialize the positions of gorillas, which facilitates the population diversity and establishes a good foundation for global search. Then, in order to avoid getting trapped in the local optimum,… More >

  • Research Article

    Efficient Numerical Scheme for the Solution of HIV Infection CD4+ T-Cells Using Haar Wavelet Technique

    Rohul Amin1, Şuayip Yüzbası2,*, Shah Nazir3
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.019154
    Abstract In this paper, Haar collocation algorithm is developed for the solution of first-order of HIV infection CD4+ T-Cells model. In this technique, the derivative in the nonlinear model is approximated by utilizing Haar functions. The value of the unknown function is obtained by the process of integration. Error estimation is also discussed, which aims to reduce the error of numerical solutions. The numerical results show that the method is simply applicable. The results are compared with Runge-Kutta technique, Bessel collocation technique, LADM-Pade and Galerkin technique available in the literature. The results show that the Haar technique is easy, precise and… More >

  • Research Article

    Partitioning of Water Distribution Network into District Metered Areas Using Existing Valves

    Aniket N. Sharma1, Shilpa R. Dongre1, Rajesh Gupta1, Prerna Pandey1, Neeraj Dhanraj Bokde2,*
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.018867
    (This article belongs to this Special Issue: Computer Modeling for Smart Cities Applications)
    Abstract Water distribution network (WDN) leakage management has received increased attention in recent years. One of the most successful leakage-control strategies is to divide the network into District Metered Areas (DMAs). As a multi-staged technique, the generation of DMAs is a difficult task in design and implementation (i.e., clustering, sectorization, and performance evaluation). Previous studies on DMAs implementation did not consider the potential use of existing valves in achieving the objective. In this work, a methodology is proposed for detecting clusters and reducing the cost of additional valves and DMA sectorization by considering existing valves as much as possible. The procedure… More >

  • Research Article

    A Lightweight and Robust User Authentication Protocol with User Anonymity for IoT-Based Healthcare

    Chien-Ming Chen1,*, Shuangshuang Liu1, Shehzad Ashraf Chaudhry2, Yeh-Cheng Chen3, Muhammad Asghar khan4
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.018749
    (This article belongs to this Special Issue: Internet of Things in Healthcare and Health: Security and Privacy)
    Abstract With the rise of the Internet of Things (IoT), the word “intelligent medical care” has increasingly become a major vision. Intelligent medicine adopts the most advanced IoT technology to realize the interaction between patients and people, medical institutions, and medical equipment. However, with the openness of network transmission, the security and privacy of information transmission have become a major problem. Recently, Masud et al. proposed a lightweight anonymous user authentication protocol for IoT medical treatment, claiming that their method can resist various attacks. However, through analysis of the protocol, we observed that their protocol cannot effectively resist privileged internal attacks,… More >

  • Research Article

    Neutrosophic κ-Structures in Ordered Semigroups

    G. Muhiuddin1,*, K. Porselvi2, B. Elavarasan2, D. Al-Kadi3
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.018615
    (This article belongs to this Special Issue: Advances in Neutrosophic and Plithogenic Sets for Engineering and Sciences: Theory, Models, and Applications (ANPSESTMA))
    Abstract In general, ordered algebraic structures, particularly ordered semigroups, play an important role in fuzzification in many applied areas, such as computer science, formal languages, coding theory, error correction, etc. Nowadays, the concept of ambiguity is important in dealing with a variety of issues related to engineering modeling problems, network theory, decision-making problems in real-life situations, and so on. Several theories have been developed by various researchers to overcome the difficulties that arise from uncertainty, including fuzzy sets, intuitionistic fuzzy sets, probability, soft sets, neutrosophic sets, and many more. In this paper, we focus solely on neutrosophic set theory. In ordered… More >

  • Research Article

    Mu-Net: Multi-Path Upsampling Convolution Network for Medical Image Segmentation

    Jia Chen1, Zhiqiang He1, Dayong Zhu1, Bei Hui1,*, Rita Yi Man Li2, Xiao-Guang Yue2,3,4
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.018565
    Abstract Medical image segmentation plays an important role in clinical diagnosis, quantitative analysis, and treatment process. Since 2015, U-Net-based approaches have been widely used for medical image segmentation. The purpose of the U-Net expansive path is to map low-resolution encoder feature maps to full input resolution feature maps. However, the consecutive deconvolution and convolutional operations in the expansive path lead to the loss of some high-level information. More high-level information can make the segmentation more accurate. In this paper, we propose MU-Net, a novel, multi-path upsampling convolution network to retain more high-level information. The MU-Net mainly consists of three parts: contracting… More >

  • Research Article

    Game Outlier Behavior Detection System Based on Dynamic Time aWarp Algorithm

    Shinjin Kang1, Soo Kyun Kim2,*
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.018413
    (This article belongs to this Special Issue: HPC with Artificial Intelligence based Deep Video Data Analytics: Models, Applications and Approaches)
    Abstract This paper proposes a methodology for using multi-modal data in gameplay to detect outlier behavior. The proposed methodology collects, synchronizes, and quantifies time-series data from webcams, mouses, and keyboards. Facial expressions are varied on a one-dimensional pleasure axis, and changes in expression in the mouth and eye areas are detected separately. Furthermore, the keyboard and mouse input frequencies are tracked to determine the interaction intensity of users. Then, we apply a dynamic time warp algorithm to detect outlier behavior. The detected outlier behavior graph patterns were the play patterns that the game designer did not intend or play patterns that… More >

  • Research Article

    Image Translation Method for Game Character Sprite Drawing

    Jong-In Choi1, Soo-Kyun Kim2, Shin-Jin Kang3,*
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.018201
    (This article belongs to this Special Issue: HPC with Artificial Intelligence based Deep Video Data Analytics: Models, Applications and Approaches)
    Abstract Two-dimensional (2D) character animation is one of the most important visual elements on which users’ interest is focused in the game field. However, 2D character animation works in the game field are mostly performed manually in two dimensions, thus generating high production costs. This study proposes a generative adversarial network based production tool that can easily and quickly generate the sprite images of 2D characters. First, we proposed a methodology to create a synthetic dataset for training using images from the real world in the game resource production field where machine learning datasets are insufficient. In addition, we have enabled… More >

  • Research Article

    k-Order Fibonacci Polynomials on AES-Like Cryptology

    Mustafa Asci, Suleyman Aydinyuz*
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.017898
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract The Advanced Encryption Standard (AES) is the most widely used symmetric cipher today. AES has an important place in cryptology. Finite field, also known as Galois Fields, are cornerstones for understanding any cryptography. This encryption method on AES is a method that uses polynomials on Galois fields. In this paper, we generalize the AES-like cryptology on 2 × 2 matrices. We redefine the elements of k-order Fibonacci polynomials sequences using a certain irreducible polynomial in our cryptology algorithm. So, this cryptology algorithm is called AES-like cryptology on the k-order Fibonacci polynomial matrix. More >

  • Research Article

    Degenerate s-Extended Complete and Incomplete Lah-Bell Polynomials

    Hye Kyung Kim1,*, Dae Sik Lee2
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.017616
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract Degenerate versions of special polynomials and numbers applied to social problems, physics, and applied mathematics have been studied variously in recent years. Moreover, the (s-)Lah numbers have many other interesting applications in analysis and combinatorics. In this paper, we divide two parts. We first introduce new types of both degenerate incomplete and complete s-Bell polynomials respectively and investigate some properties of them respectively. Second, we introduce the degenerate versions of complete and incomplete Lah-Bell polynomials as multivariate forms for a new type of degenerate s-extended Lah-Bell polynomials and numbers respectively. We investigate relations between these polynomials and degenerate incomplete and… More >

  • Research Article

    Modeling the Spread of Tuberculosis with Piecewise Differential Operators

    Abdon Atangana1,2, Ilknur Koca3,*
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.019221
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract Very recently, a new concept was introduced to capture crossover behaviors that exhibit changes in patterns. The aim was to model real-world problems exhibiting crossover from one process to another, for example, randomness to a power law. The concept was called piecewise calculus, as differential and integral operators are defined piece wisely. These behaviors have been observed in the spread of several infectious diseases, for example, tuberculosis. Therefore, in this paper, we aim at modeling the spread of tuberculosis using the concept of piecewise modeling. Several cases are considered, conditions under which the unique system solution is obtained are presented… More >

  • Research Article

    On Degenerate Array Type Polynomials

    Lan Wu1, Xue-Yan Chen1, Muhammet Cihat Dağli2, Feng Qi3,4,*
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.018778
    (This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
    Abstract In the paper, with the help of the Faá di Bruno formula and an identity of the Bell polynomials of the second kind, the authors define degenerate λ-array type polynomials, establish two explicit formulas, and present several recurrence relations of degenerate λ-array type polynomials and numbers. More >

  • Research Article

    Skew t Distribution-Based Nonlinear Filter with Asymmetric Measurement Noise Using Variational Bayesian Inference

    Chen Xu1, Yawen Mao2, Hongtian Chen3,*, Hongfeng Tao1, Fei Liu1
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2021.019027
    (This article belongs to this Special Issue: Advanced on Modeling and State Estimation for Industrial Processes)
    Abstract This paper is focused on the state estimation problem for nonlinear systems with unknown statistics of measurement noise. Based on the cubature Kalman filter, we propose a new nonlinear filtering algorithm that employs a skew t distribution to characterize the asymmetry of the measurement noise. The system states and the statistics of skew t noise distribution, including the shape matrix, the scale matrix, and the degree of freedom (DOF) are estimated jointly by employing variational Bayesian (VB) inference. The proposed method is validated in a target tracking example. Results of the simulation indicate that the proposed nonlinear filter can perform… More >

  • Research Article

    Parameter Estimation Based on Censored Data under Partially Accelerated Life Testing for Hybrid Systems due to Unknown Failure Causes

    Mustafa Kamal*
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.017532
    Abstract In general, simple subsystems like series or parallel are integrated to produce a complex hybrid system. The reliability of a system is determined by the reliability of its constituent components. It is often extremely difficult or impossible to get specific information about the component that caused the system to fail. Unknown failure causes are instances in which the actual cause of system failure is unknown. On the other side, thanks to current advanced technology based on computers, automation, and simulation, products have become incredibly dependable and trustworthy, and as a result, obtaining failure data for testing such exceptionally reliable items… More >

  • Research Article

    Complex Network Formation and Analysis of Online Social Media Systems

    Hafiz Abid Mahmood Malik*
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2022.018015
    (This article belongs to this Special Issue: Application of Computer Modeling and Simulation in Social Complex System)
    Abstract To discover and identify the influential nodes in any complex network has been an important issue. It is a significant factor in order to control over the network. Through control on a network, any information can be spread and stopped in a short span of time. Both targets can be achieved, since network of information can be extended and as well destroyed. So, information spread and community formation have become one of the most crucial issues in the world of SNA (Social Network Analysis). In this work, the complex network of twitter social network has been formalized and results are… More >

  • Research Article

    Strengthened Initialization of Adaptive Cross-Generation Differential Evolution

    Wei Wan1, Gaige Wang1,2,3,*, Junyu Dong1
    CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2021.017987
    (This article belongs to this Special Issue: Swarm Intelligence and Applications in Combinatorial Optimization)
    Abstract Adaptive Cross-Generation Differential Evolution (ACGDE) is a recently-introduced algorithm for solving multiobjective problems with remarkable performance compared to other evolutionary algorithms (EAs). However, its convergence and diversity are not satisfactory compared with the latest algorithms. In order to adapt to the current environment, ACGDE requires improvements in many aspects, such as its initialization and mutant operator. In this paper, an enhanced version is proposed, namely SIACGDE. It incorporates a strengthened initialization strategy and optimized parameters in contrast to its predecessor. These improvements make the direction of crossgeneration mutation more clearly and the ability of searching more efficiently. The experiments show… More >