Home / Journals / CMC / Vol.67, No.2, 2021
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  • Open AccessOpen Access

    ARTICLE

    Recognition and Detection of Diabetic Retinopathy Using Densenet-65 Based Faster-RCNN

    Saleh Albahli1, Tahira Nazir2,*, Aun Irtaza2, Ali Javed3
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1333-1351, 2021, DOI:10.32604/cmc.2021.014691
    (This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
    Abstract Diabetes is a metabolic disorder that results in a retinal complication called diabetic retinopathy (DR) which is one of the four main reasons for sightlessness all over the globe. DR usually has no clear symptoms before the onset, thus making disease identification a challenging task. The healthcare industry may face unfavorable consequences if the gap in identifying DR is not filled with effective automation. Thus, our objective is to develop an automatic and cost-effective method for classifying DR samples. In this work, we present a custom Faster-RCNN technique for the recognition and classification of DR… More >

  • Open AccessOpen Access

    ARTICLE

    Adaptation of Vehicular Ad hoc Network Clustering Protocol for Smart Transportation

    Masood Ahmad1, Abdul Hameed2, Fasee Ullah3,*, Ishtiaq Wahid1, Atif Khan4, M. Irfan Uddin5, Shafiq Ahmad6, Ahmed M. El-Sherbeeny6
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1353-1368, 2021, DOI:10.32604/cmc.2021.014237
    (This article belongs to the Special Issue: Deep Learning and Parallel Computing for Intelligent and Efficient IoT)
    Abstract Clustering algorithms optimization can minimize topology maintenance overhead in large scale vehicular Ad hoc networks (VANETs) for smart transportation that results from dynamic topology, limited resources and non-centralized architecture. The performance of a clustering algorithm varies with the underlying mobility model to address the topology maintenance overhead issue in VANETs for smart transportation. To design a robust clustering algorithm, careful attention must be paid to components like mobility models and performance objectives. A clustering algorithm may not perform well with every mobility pattern. Therefore, we propose a supervisory protocol (SP) that observes the mobility pattern… More >

  • Open AccessOpen Access

    ARTICLE

    Computational Microfluidic Channel for Separation of Escherichia coli from Blood-Cells

    Chinnapalli Likith Kumar1,*, A. Vimala Juliet1, Bandaru Ramakrishna2, Shubhangi Chakraborty1, Mazin Abed Mohammed3, Kalakanda Alfred Sunny4
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1369-1384, 2021, DOI:10.32604/cmc.2021.015116
    (This article belongs to the Special Issue: Retrospective Big Data Analytics in Radiological Imaging for Precision Medicine)
    Abstract Microfluidic channels play a vital role in separation of analytes of interest such as bacteria and platelet cells, etc., in various biochemical diagnosis procedures including urinary tract infections (UTI) and bloodstream infections. This paper presents the multi physics computational model specifically designed to study the effects of design parameters of a microfluidics channel for the separation of Escherichia coli (E. coli) from various blood constituents including red blood cells (RBC) and platelets. A standard two inlet and a two outlet microchannel of length 805 m with a channel width of 40 m is simulated. The effect of… More >

  • Open AccessOpen Access

    ARTICLE

    A Fractal-Fractional Model for the MHD Flow of Casson Fluid in a Channel

    Nadeem Ahmad Sheikh1,2, Dennis Ling Chuan Ching1, Thabet Abdeljawad3,4,5, Ilyas Khan6,*, Muhammad Jamil7,8, Kottakkaran Sooppy Nisar9
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1385-1398, 2021, DOI:10.32604/cmc.2021.011986
    Abstract An emerging definition of the fractal-fractional operator has been used in this study for the modeling of Casson fluid flow. The magnetohydrodynamics flow of Casson fluid has cogent in a channel where the motion of the upper plate generates the flow while the lower plate is at a static position. The proposed model is non-dimensionalized using the Pi-Buckingham theorem to reduce the complexity in solving the model and computation time. The non-dimensional fractal-fractional model with the power-law kernel has been solved through the Laplace transform technique. The Mathcad software has been used for illustration of… More >

  • Open AccessOpen Access

    ARTICLE

    Simulation, Modeling, and Optimization of Intelligent Kidney Disease Predication Empowered with Computational Intelligence Approaches

    Abdul Hannan Khan1,2, Muhammad Adnan Khan3,*, Sagheer Abbas2, Shahan Yamin Siddiqui1,2, Muhammad Aanwar Saeed4, Majed Alfayad5, Nouh Sabri Elmitwally6,7
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1399-1412, 2021, DOI:10.32604/cmc.2021.012737
    Abstract Artificial intelligence (AI) is expanding its roots in medical diagnostics. Various acute and chronic diseases can be identified accurately at the initial level by using AI methods to prevent the progression of health complications. Kidney diseases are producing a high impact on global health and medical practitioners are suggested that the diagnosis at earlier stages is one of the foremost approaches to avert chronic kidney disease and renal failure. High blood pressure, diabetes mellitus, and glomerulonephritis are the root causes of kidney disease. Therefore, the present study is proposed a set of multiple techniques such… More >

  • Open AccessOpen Access

    ARTICLE

    Prediction of Time Series Empowered with a Novel SREKRLS Algorithm

    Bilal Shoaib1, Yasir Javed2, Muhammad Adnan Khan3,*, Fahad Ahmad4, Rizwan Majeed5, Muhammad Saqib Nawaz1, Muhammad Adeel Ashraf6, Abid Iqbal2, Muhammad Idrees7
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1413-1427, 2021, DOI:10.32604/cmc.2021.015099
    Abstract For the unforced dynamical non-linear statespace model, a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article. The proposed algorithm lends itself towards the parallel implementation as in the FPGA systems. With the help of an ortho-normal triangularization method, which relies on numerically stable givens rotation, matrix inversion causes a computational burden, is reduced. Matrix computation possesses many excellent numerical properties such as singularity, symmetry, skew symmetry, and triangularity is achieved by using this algorithm. The proposed method is validated for the prediction of stationary and… More >

  • Open AccessOpen Access

    ARTICLE

    Intrusion Detection System Using FKNN and Improved PSO

    Raniyah Wazirali*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1429-1445, 2021, DOI:10.32604/cmc.2021.014172
    Abstract Intrusion detection system (IDS) techniques are used in cybersecurity to protect and safeguard sensitive assets. The increasing network security risks can be mitigated by implementing effective IDS methods as a defense mechanism. The proposed research presents an IDS model based on the methodology of the adaptive fuzzy k-nearest neighbor (FKNN) algorithm. Using this method, two parameters, i.e., the neighborhood size (k) and fuzzy strength parameter (m) were characterized by implementing the particle swarm optimization (PSO). In addition to being used for FKNN parametric optimization, PSO is also used for selecting the conditional feature subsets for… More >

  • Open AccessOpen Access

    ARTICLE

    MMALE—A Methodology for Malware Analysis in Linux Environments

    José Javier de Vicente Mohino1, Javier Bermejo Higuera1, Juan Ramón Bermejo Higuera1, Juan Antonio Sicilia Montalvo1,*, Manuel Sánchez Rubio1, José Javier Martínez Herraiz2
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1447-1469, 2021, DOI:10.32604/cmc.2021.014596
    (This article belongs to the Special Issue: Current trends and Advancements for next-generation secure Industrial IoT)
    Abstract In a computer environment, an operating system is prone to malware, and even the Linux operating system is not an exception. In recent years, malware has evolved, and attackers have become more qualified compared to a few years ago. Furthermore, Linux-based systems have become more attractive to cybercriminals because of the increasing use of the Linux operating system in web servers and Internet of Things (IoT) devices. Windows is the most employed OS, so most of the research efforts have been focused on its malware protection rather than on other operating systems. As a result,… More >

  • Open AccessOpen Access

    ARTICLE

    Evaluating the Impact of Prediction Techniques: Software Reliability Perspective

    Kavita Sahu1, Fahad A. Alzahrani2, R. K. Srivastava1, Rajeev Kumar3,4,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1471-1488, 2021, DOI:10.32604/cmc.2021.014868
    Abstract Maintaining software reliability is the key idea for conducting quality research. This can be done by having less complex applications. While developers and other experts have made significant efforts in this context, the level of reliability is not the same as it should be. Therefore, further research into the most detailed mechanisms for evaluating and increasing software reliability is essential. A significant aspect of growing the degree of reliable applications is the quantitative assessment of reliability. There are multiple statistical as well as soft computing methods available in literature for predicting reliability of software. However,… More >

  • Open AccessOpen Access

    ARTICLE

    Blockchain Technology Based Information Classification Management Service

    Gi-Wan Hong1, Jeong-Wook Kim1, Hangbae Chang2,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1489-1501, 2021, DOI:10.32604/cmc.2021.013344
    (This article belongs to the Special Issue: Innovation of Blockchain Technology)
    Abstract Hyper-connectivity in Industry 4.0 has resulted in not only a rapid increase in the amount of information, but also the expansion of areas and assets to be protected. In terms of information security, it has led to an enormous economic cost due to the various and numerous security solutions used in protecting the increased assets. Also, it has caused difficulties in managing those issues due to reasons such as mutual interference, countless security events and logs’ data, etc. Within this security environment, an organization should identify and classify assets based on the value of data… More >

  • Open AccessOpen Access

    ARTICLE

    New Improved Ranked Set Sampling Designs with an Application to Real Data

    Amer Ibrahim Al-Omari1, Ibrahim M. Almanjahie2,3,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1503-1522, 2021, DOI:10.32604/cmc.2021.015047
    (This article belongs to the Special Issue: Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
    Abstract This article proposes two new Ranked Set Sampling (RSS) designs for estimating the population parameters: Simple Z Ranked Set Sampling (SZRSS) and Generalized Z Ranked Set Sampling (GZRSS). These designs provide unbiased estimators for the mean of symmetric distributions. It is shown that for non-uniform symmetric distributions, the estimators of the mean under the suggested designs are more efficient than those obtained by RSS, Simple Random Sampling (SRS), extreme RSS and truncation based RSS designs. Also, the proposed RSS schemes outperform other RSS schemes and provide more efficient estimates than their competitors under imperfect rankings. More >

  • Open AccessOpen Access

    ARTICLE

    Novel Universal Windowing Multicarrier Waveform for 5G Systems

    Ahmed Hammoodi1, Lukman Audah1,*, Montadar Abas Taher2, Mazin Abed Mohammed3, Mustafa S. Aljumaily4, Adeeb Salh1, Shipun A. Hamzah1
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1523-1536, 2021, DOI:10.32604/cmc.2021.014041
    (This article belongs to the Special Issue: Advanced 5G Communication System for Transforming Health Care)
    Abstract Fifth Generation (5G) systems aim to improve flexibility, coexistence and diverse service in several aspects to achieve the emerging applications requirements. Windowing and filtering of the traditional multicarrier waveforms are now considered common sense when designing more flexible waveforms. This paper proposed a Universal Windowing Multi-Carrier (UWMC) waveform design platform that is flexible, providing more easily coexists with different pulse shapes, and reduces the Out of Band Emissions (OOBE), which is generated by the traditional multicarrier methods that used in the previous generations of the mobile technology. The novel proposed approach is different from other… More >

  • Open AccessOpen Access

    ARTICLE

    M-IDM: A Multi-Classification Based Intrusion Detection Model in Healthcare IoT

    Jae Dong Lee1,2, Hyo Soung Cha1, Shailendra Rathore2, Jong Hyuk Park2,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1537-1553, 2021, DOI:10.32604/cmc.2021.014774
    (This article belongs to the Special Issue: Machine Learning-based Secured and Privacy-preserved Smart City)
    Abstract In recent years, the application of a smart city in the healthcare sector via loT systems has continued to grow exponentially and various advanced network intrusions have emerged since these loT devices are being connected. Previous studies focused on security threat detection and blocking technologies that rely on testbed data obtained from a single medical IoT device or simulation using a well-known dataset, such as the NSL-KDD dataset. However, such approaches do not reflect the features that exist in real medical scenarios, leading to failure in potential threat detection. To address this problem, we proposed… More >

  • Open AccessOpen Access

    ARTICLE

    Estimation Performance for the Cubature Particle Filter under Nonlinear/Non-Gaussian Environments

    Dah-Jing Jwo1,*, Chien-Hao Tseng2
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1555-1575, 2021, DOI:10.32604/cmc.2021.014875
    Abstract This paper evaluates the state estimation performance for processing nonlinear/non-Gaussian systems using the cubature particle filter (CPF), which is an estimation algorithm that combines the cubature Kalman filter (CKF) and the particle filter (PF). The CPF is essentially a realization of PF where the third-degree cubature rule based on numerical integration method is adopted to approximate the proposal distribution. It is beneficial where the CKF is used to generate the importance density function in the PF framework for effectively resolving the nonlinear/non-Gaussian problems. Based on the spherical-radial transformation to generate an even number of equally… More >

  • Open AccessOpen Access

    ARTICLE

    Medical Image Compression Based on Wavelets with Particle Swarm Optimization

    Monagi H. Alkinani1,*, E. A. Zanaty2, Sherif M. Ibrahim3
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1577-1593, 2021, DOI:10.32604/cmc.2021.014803
    Abstract This paper presents a novel method utilizing wavelets with particle swarm optimization (PSO) for medical image compression. Our method utilizes PSO to overcome the wavelets discontinuity which occurs when compressing images using thresholding. It transfers images into subband details and approximations using a modified Haar wavelet (MHW), and then applies a threshold. PSO is applied for selecting a particle assigned to the threshold values for the subbands. Nine positions assigned to particles values are used to represent population. Every particle updates its position depending on the global best position (gbest) (for all details subband) and More >

  • Open AccessOpen Access

    ARTICLE

    Using Susceptible-Exposed-Infectious-Recovered Model to Forecast Coronavirus Outbreak

    Debabrata Dansana1, Raghvendra Kumar1, Arupa Parida1, Rohit Sharma2, Janmejoy Das Adhikari1, Hiep Van Le3,*, Binh Thai Pham4, Krishna Kant Singh5, Biswajeet Pradhan6,7,8,9
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1595-1612, 2021, DOI:10.32604/cmc.2021.012646
    (This article belongs to the Special Issue: COVID-19 impacts on Software Engineering industry and research community)
    Abstract The Coronavirus disease 2019 (COVID-19) outbreak was first discovered in Wuhan, China, and it has since spread to more than 200 countries. The World Health Organization proclaimed COVID-19 a public health emergency of international concern on January 30, 2020. Normally, a quickly spreading infection that could jeopardize the well-being of countless individuals requires prompt action to forestall the malady in a timely manner. COVID-19 is a major threat worldwide due to its ability to rapidly spread. No vaccines are yet available for COVID-19. The objective of this paper is to examine the worldwide COVID-19 pandemic,… More >

  • Open AccessOpen Access

    ARTICLE

    COVID-19 Public Sentiment Insights: A Text Mining Approach to the Gulf Countries

    Saleh Albahli1, Ahmad Algsham1, Shamsulhaq Aeraj1, Muath Alsaeed1, Muath Alrashed1, Hafiz Tayyab Rauf2,*, Muhammad Arif3, Mazin Abed Mohammed4
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1613-1627, 2021, DOI:10.32604/cmc.2021.014265
    (This article belongs to the Special Issue: Intelligent techniques for energy efficient service management in Edge computing)
    Abstract Social media has been the primary source of information from mainstream news agencies due to the large number of users posting their feedback. The COVID-19 outbreak did not only bring a virus with it but it also brought fear and uncertainty along with inaccurate and misinformation spread on social media platforms. This phenomenon caused a state of panic among people. Different studies were conducted to stop the spread of fake news to help people cope with the situation. In this paper, a semantic analysis of three levels (negative, neutral, and positive) is used to gauge… More >

  • Open AccessOpen Access

    ARTICLE

    Exploiting Deep Learning Techniques for Colon Polyp Segmentation

    Daniel Sierra-Sosa1,*, Sebastian Patino-Barrientos2, Begonya Garcia-Zapirain3, Cristian Castillo-Olea3, Adel Elmaghraby1
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1629-1644, 2021, DOI:10.32604/cmc.2021.013618
    (This article belongs to the Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
    Abstract As colon cancer is among the top causes of death, there is a growing interest in developing improved techniques for the early detection of colon polyps. Given the close relation between colon polyps and colon cancer, their detection helps avoid cancer cases. The increment in the availability of colorectal screening tests and the number of colonoscopies have increased the burden on the medical personnel. In this article, the application of deep learning techniques for the detection and segmentation of colon polyps in colonoscopies is presented. Four techniques were implemented and evaluated: Mask-RCNN, PANet, Cascade R-CNN… More >

  • Open AccessOpen Access

    ARTICLE

    Epidemiologic Evolution Platform Using Integrated Modeling and Geographic Information System

    Adrian Brezulianu1, Oana Geman2,*, Muhammad Arif3, Iuliana Chiuchisan2, Octavian Postolache2, Guojun Wang3
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1645-1663, 2021, DOI:10.32604/cmc.2021.014225
    (This article belongs to the Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
    Abstract At the international level, a major effort is being made to optimize the flow of data and information for health systems management. The studies show that medical and economic efficiency is strongly influenced by the level of development and complexity of implementing an integrated system of epidemiological monitoring and modeling. The solution proposed and described in this paper is addressed to all public and private institutions involved in the fight against the COVID-19 pandemic, using recognized methods and standards in this field. The Green-Epidemio is a platform adaptable to the specific features of any public… More >

  • Open AccessOpen Access

    ARTICLE

    PeachNet: Peach Diseases Detection for Automatic Harvesting

    Wael Alosaimi1,*, Hashem Alyami2, M. Irfan Uddin3
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1665-1677, 2021, DOI:10.32604/cmc.2021.014950
    (This article belongs to the Special Issue: Deep Learning and Parallel Computing for Intelligent and Efficient IoT)
    Abstract To meet the food requirements of the seven billion people on Earth, multiple advancements in agriculture and industry have been made. The main threat to food items is from diseases and pests which affect the quality and quantity of food. Different scientific mechanisms have been developed to protect plants and fruits from pests and diseases and to increase the quantity and quality of food. Still these mechanisms require manual efforts and human expertise to diagnose diseases. In the current decade Artificial Intelligence is used to automate different processes, including agricultural processes, such as automatic harvesting.… More >

  • Open AccessOpen Access

    ARTICLE

    Technology Landscape for Epidemiological Prediction and Diagnosis of COVID-19

    Siddhant Banyal1, Rinky Dwivedi2, Koyel Datta Gupta2, Deepak Kumar Sharma3,*, Fadi Al-Turjman4, Leonardo Mostarda5
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1679-1696, 2021, DOI:10.32604/cmc.2021.014387
    (This article belongs to the Special Issue: COVID-19 impacts on Software Engineering industry and research community)
    Abstract The COVID-19 outbreak initiated from the Chinese city of Wuhan and eventually affected almost every nation around the globe. From China, the disease started spreading to the rest of the world. After China, Italy became the next epicentre of the virus and witnessed a very high death toll. Soon nations like the USA became severely hit by SARS-CoV-2 virus. The World Health Organisation, on 11th March 2020, declared COVID-19 a pandemic. To combat the epidemic, the nations from every corner of the world has instituted various policies like physical distancing, isolation of infected population and… More >

  • Open AccessOpen Access

    ARTICLE

    QI-BRiCE: Quality Index for Bleeding Regions in Capsule Endoscopy Videos

    Muhammad Arslan Usman1, Muhammad Rehan Usman2, Gandeva Bayu Satrya3, Muhammad Ashfaq Khan4, Christos Politis1, Nada Philip1, Soo Young Shin5,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1697-1712, 2021, DOI:10.32604/cmc.2021.014696
    (This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
    Abstract With the advent in services such as telemedicine and telesurgery, provision of continuous quality monitoring for these services has become a challenge for the network operators. Quality standards for provision of such services are application specific as medical imagery is quite different than general purpose images and videos. This paper presents a novel full reference objective video quality metric that focuses on estimating the quality of wireless capsule endoscopy (WCE) videos containing bleeding regions. Bleeding regions in gastrointestinal tract have been focused in this research, as bleeding is one of the major reasons behind several… More >

  • Open AccessOpen Access

    ARTICLE

    Optimality of Solution with Numerical Investigation for Coronavirus Epidemic Model

    Naveed Shahid1,2, Dumitru Baleanu3,4,5, Nauman Ahmed1,2, Tahira Sumbal Shaikh6, Ali Raza7,*, Muhammad Sajid Iqbal1, Muhammad Rafiq8, Muhammad Aziz-ur Rehman2
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1713-1728, 2021, DOI:10.32604/cmc.2021.014191
    Abstract The novel coronavirus disease, coined as COVID-19, is a murderous and infectious disease initiated from Wuhan, China. This killer disease has taken a large number of lives around the world and its dynamics could not be controlled so far. In this article, the spatio-temporal compartmental epidemic model of the novel disease with advection and diffusion process is projected and analyzed. To counteract these types of diseases or restrict their spread, mankind depends upon mathematical modeling and medicine to reduce, alleviate, and anticipate the behavior of disease dynamics. The existence and uniqueness of the solution for… More >

  • Open AccessOpen Access

    ARTICLE

    Weighted Gauss-Seidel Precoder for Downlink Massive MIMO Systems

    Jun-Yong Jang1, Won-Seok Lee1, Jae-Hyun Ro1, Young-Hawn You2, Hyoung-Kyu Song1,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1729-1745, 2021, DOI:10.32604/cmc.2021.015424
    Abstract In this paper, a novel precoding scheme based on the Gauss-Seidel (GS) method is proposed for downlink massive multiple-input multiple-output (MIMO) systems. The GS method iteratively approximates the matrix inversion and reduces the overall complexity of the precoding process. In addition, the GS method shows a fast convergence rate to the Zero-forcing (ZF) method that requires an exact invertible matrix. However, to satisfy demanded error performance and converge to the error performance of the ZF method in the practical condition such as spatially correlated channels, more iterations are necessary for the GS method and increase… More >

  • Open AccessOpen Access

    ARTICLE

    Multi-Gigabit CO-OFDM System over SMF and MMF Links for 5G URLLC Backhaul Network

    Amir Haider1, MuhibUr Rahman2, Tayyaba Khan3, Muhammad Tabish Niaz1, Hyung Seok Kim1,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1747-1758, 2021, DOI:10.32604/cmc.2021.015611
    Abstract The 5G cellular network aims at providing three major services: Massive machine-type communication (mMTC), ultra-reliable low-latency communications (URLLC), and enhanced-mobile-broadband (eMBB). Among these services, the URLLC and eMBB require strict end-to-end latency of 1 ms while maintaining 99.999% reliability, and availability of extremely high data rates for the users, respectively. One of the critical challenges in meeting these requirements is to upgrade the existing optical fiber backhaul network interconnecting the base stations with a multigigabit capacity, low latency and very high reliability system. To address this issue, we have numerically analyzed 100 Gbit/s coherent optical… More >

  • Open AccessOpen Access

    ARTICLE

    Efficient Algorithms for Cache-Throughput Analysis in Cellular-D2D 5G Networks

    Nasreen Anjum1,*, Zhaohui Yang1, Imran Khan2, Mahreen Kiran3, Falin Wu4, Khaled Rabie5, Shikh Muhammad Bahaei1
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1759-1780, 2021, DOI:10.32604/cmc.2021.014635
    Abstract In this paper, we propose a two-tiered segment-based Device-to-Device (S-D2D) caching approach to decrease the startup and playback delay experienced by Video-on-Demand (VoD) users in a cellular network. In the S-D2D caching approach cache space of each mobile device is divided into two cache-blocks. The first cache-block reserve for caching and delivering the beginning portion of the most popular video files and the second cache-block caches the latter portion of the requested video files ‘fully or partially’ depending on the users’ video watching behaviour and popularity of videos. In this approach before caching, video is… More >

  • Open AccessOpen Access

    ARTICLE

    Position Vectors Based Efficient Indoor Positioning System

    Ayesha Javed1, Mir Yasir Umair1,*, Alina Mirza1, Abdul Wakeel1, Fazli Subhan2, Wazir Zada Khan3
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1781-1799, 2021, DOI:10.32604/cmc.2021.015229
    (This article belongs to the Special Issue: Green IoT Networks using Machine Learning, Deep Learning Models)
    Abstract With the advent and advancements in the wireless technologies, Wi-Fi fingerprinting-based Indoor Positioning System (IPS) has become one of the most promising solutions for localization in indoor environments. Unlike the outdoor environment, the lack of line-of-sight propagation in an indoor environment keeps the interest of the researchers to develop efficient and precise positioning systems that can later be incorporated in numerous applications involving Internet of Things (IoTs) and green computing. In this paper, we have proposed a technique that combines the capabilities of multiple algorithms to overcome the complexities experienced indoors. Initially, in the database… More >

  • Open AccessOpen Access

    ARTICLE

    Adaptive Signal Enhancement Unit for EEG Analysis in Remote Patient Care Monitoring Systems

    Ch. Srinivas1,*, K. Chandrabhushana Rao2
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1801-1817, 2021, DOI:10.32604/cmc.2021.014981
    (This article belongs to the Special Issue: Advances in Intelligent and Knowledge based systems for Elderly and Remote Patient Care Monitoring)
    Abstract In this paper we propose an efficient process of physiological artifact elimination methodology from brain waves (BW), which are also commonly known as electroencephalogram (EEG) signal. In a clinical environment during the acquisition of BW several artifacts contaminates the actual BW component. This leads to inaccurate and ambiguous diagnosis. As the statistical nature of the EEG signal is more non-stationery, adaptive filtering is the more promising method for the process of artifact elimination. In clinical conditions, the conventional adaptive techniques require many numbers of computational operations and leads to data samples overlapping and instability of… More >

  • Open AccessOpen Access

    REVIEW

    Automated Test Case Generation from Requirements: A Systematic Literature Review

    Ahmad Mustafa1, Wan M. N. Wan-Kadir1, Noraini Ibrahim1, Muhammad Arif Shah3,*, Muhammad Younas2, Atif Khan4, Mahdi Zareei5, Faisal Alanazi6
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1819-1833, 2021, DOI:10.32604/cmc.2021.014391
    Abstract Software testing is an important and cost intensive activity in software development. The major contribution in cost is due to test case generations. Requirement-based testing is an approach in which test cases are derivative from requirements without considering the implementation’s internal structure. Requirement-based testing includes functional and nonfunctional requirements. The objective of this study is to explore the approaches that generate test cases from requirements. A systematic literature review based on two research questions and extensive quality assessment criteria includes studies. The study identifies 30 primary studies from 410 studies spanned from 2000 to 2018.… More >

  • Open AccessOpen Access

    ARTICLE

    Analyzing COVID-19 Impact on the Researchers Productivity through Their Perceptions

    Syeda Javeria Shoukat1, Humaira Afzal2, Muhammad Rafiq Mufti3, Muhammad Khalid Sohail4, Dost Muhammad Khan5, Nadeem Akhtar5, Shahid Hussain6,*, Mansoor Ahmed1
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1835-1847, 2021, DOI:10.32604/cmc.2021.014397
    (This article belongs to the Special Issue: COVID-19 impacts on Software Engineering industry and research community)
    Abstract Context: Since the end of 2019, the COVID-19 pandemic had a worst impact on world’s economy, healthcare, and education. There are several aspects where the impact of COVID-19 could be visualized. Among these, one aspect is the productivity of researcher, which plays a significant role in the success of an organization. Problem: There are several factors that could be aligned with the researcher’s productivity of each domain and whose analysis through researcher’s feedback could be beneficial for decision makers in terms of their decision making and implementation of mitigation plans for the success of an organization. Method:More >

  • Open AccessOpen Access

    ARTICLE

    Diabetes Type 2: Poincaré Data Preprocessing for Quantum Machine Learning

    Daniel Sierra-Sosa1,*, Juan D. Arcila-Moreno2, Begonya Garcia-Zapirain3, Adel Elmaghraby1
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1849-1861, 2021, DOI:10.32604/cmc.2021.013196
    (This article belongs to the Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
    Abstract Quantum Machine Learning (QML) techniques have been recently attracting massive interest. However reported applications usually employ synthetic or well-known datasets. One of these techniques based on using a hybrid approach combining quantum and classic devices is the Variational Quantum Classifier (VQC), which development seems promising. Albeit being largely studied, VQC implementations for “real-world” datasets are still challenging on Noisy Intermediate Scale Quantum devices (NISQ). In this paper we propose a preprocessing pipeline based on Stokes parameters for data mapping. This pipeline enhances the prediction rates when applying VQC techniques, improving the feasibility of solving classification More >

  • Open AccessOpen Access

    ARTICLE

    High Security for De-Duplicated Big Data Using Optimal SIMON Cipher

    A. Muthumari1, J. Banumathi2, S. Rajasekaran3, P. Vijayakarthik4, K. Shankar5, Irina V. Pustokhina6, Denis A. Pustokhin7,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1863-1879, 2021, DOI:10.32604/cmc.2021.013614
    Abstract Cloud computing offers internet location-based affordable, scalable, and independent services. Cloud computing is a promising and a cost-effective approach that supports big data analytics and advanced applications in the event of forced business continuity events, for instance, pandemic situations. To handle massive information, clusters of servers are required to assist the equipment which enables streamlining the widespread quantity of data, with elevated velocity and modified configurations. Data deduplication model enables cloud users to efficiently manage their cloud storage space by getting rid of redundant data stored in the server. Data deduplication also saves network bandwidth.… More >

  • Open AccessOpen Access

    ARTICLE

    Automatic Vehicle License Plate Recognition Using Optimal Deep Learning Model

    Thavavel Vaiyapuri1, Sachi Nandan Mohanty2, M. Sivaram3, Irina V. Pustokhina4, Denis A. Pustokhin5, K. Shankar6,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1881-1897, 2021, DOI:10.32604/cmc.2021.014924
    Abstract The latest advancements in highway research domain and increase inthe number of vehicles everyday led to wider exposure and attention towards the development of efficient Intelligent Transportation System (ITS). One of the popular research areas i.e., Vehicle License Plate Recognition (VLPR) aims at determining the characters that exist in the license plate of the vehicles. The VLPR process is a difficult one due to the differences in viewpoint, shapes, colors, patterns, and non-uniform illumination at the time of capturing images. The current study develops a robust Deep Learning (DL)-based VLPR model using Squirrel Search Algorithm… More >

  • Open AccessOpen Access

    ARTICLE

    Liver-Tumor Detection Using CNN ResUNet

    Muhammad Sohaib Aslam1, Muhammad Younas1, Muhammad Umar Sarwar1, Muhammad Arif Shah2,*, Atif Khan3, M. Irfan Uddin4, Shafiq Ahmad5, Muhammad Firdausi5, Mazen Zaindin6
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1899-1914, 2021, DOI:10.32604/cmc.2021.015151
    (This article belongs to the Special Issue: Deep Learning and Parallel Computing for Intelligent and Efficient IoT)
    Abstract Liver tumor is the fifth most occurring type of tumor in men and the ninth most occurring type of tumor in women according to recent reports of Global cancer statistics 2018. There are several imaging tests like Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and ultrasound that can diagnose the liver tumor after taking the sample from the tissue of the liver. These tests are costly and time-consuming. This paper proposed that image processing through deep learning Convolutional Neural Network (CNNs) ResUNet model that can be helpful for the early diagnose of tumor instead of… More >

  • Open AccessOpen Access

    ARTICLE

    Overlapping Shadow Rendering for Outdoor Augmented Reality

    Naira Elazab1, Shaker El-Sappagh2,3, Ahmed Atwan4, Hassan Soliman1, Mohammed Elmogy1, Louai Alarabi5,*, Nagham Mekky1
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1915-1932, 2021, DOI:10.32604/cmc.2021.015067
    Abstract Realism rendering methods of outdoor augmented reality (AR) is an interesting topic. Realism items in outdoor AR need advanced impacts like shadows, sunshine, and relations between unreal items. A few realistic rendering approaches were built to overcome this issue. Several of these approaches are not dealt with real-time rendering. However, the issue remains an active research topic, especially in outdoor rendering. This paper introduces a new approach to accomplish reality real-time outdoor rendering by considering the relation between items in AR regarding shadows in any place during daylight. The proposed method includes three principal stages… More >

  • Open AccessOpen Access

    ARTICLE

    Green5G: Enhancing Capacity and Coverage in Device-to-Device Communication

    Abdul Rehman Javed1,*, Rabia Abid2, Bakhtawar Aslam2, Hafiza Ammara Khalid2, Mohammad Zubair Khan3, Omar H. Alhazmi3, Muhammad Rizwan2
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1933-1950, 2021, DOI:10.32604/cmc.2021.015272
    (This article belongs to the Special Issue: Green IoT Networks using Machine Learning, Deep Learning Models)
    Abstract With the popularity of green computing and the huge usage of networks, there is an acute need for expansion of the 5G network. 5G is used where energy efficiency is the highest priority, and it can play a pinnacle role in helping every industry to hit sustainability. While in the 5G network, conventional performance guides, such as network capacity and coverage are still major issues and need improvements. Device to Device communication (D2D) communication technology plays an important role to improve the capacity and coverage of 5G technology using different techniques. The issue of energy More >

  • Open AccessOpen Access

    ARTICLE

    Dynamical Comparison of Several Third-Order Iterative Methods for Nonlinear Equations

    Obadah Said Solaiman1, Samsul Ariffin Abdul Karim2, Ishak Hashim1,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1951-1962, 2021, DOI:10.32604/cmc.2021.015344
    Abstract There are several ways that can be used to classify or compare iterative methods for nonlinear equations, for instance; order of convergence, informational efficiency, and efficiency index. In this work, we use another way, namely the basins of attraction of the method. The purpose of this study is to compare several iterative schemes for nonlinear equations. All the selected schemes are of the third-order of convergence and most of them have the same efficiency index. The comparison depends on the basins of attraction of the iterative techniques when applied on several polynomials of different degrees.… More >

  • Open AccessOpen Access

    ARTICLE

    Image-Based Lifelogging: User Emotion Perspective

    Junghyun Bum1, Hyunseung Choo1, Joyce Jiyoung Whang2,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1963-1977, 2021, DOI:10.32604/cmc.2021.014931
    Abstract Lifelog is a digital record of an individual’s daily life. It collects, records, and archives a large amount of unstructured data; therefore, techniques are required to organize and summarize those data for easy retrieval. Lifelogging has been utilized for diverse applications including healthcare, self-tracking, and entertainment, among others. With regard to the image-based lifelogging, even though most users prefer to present photos with facial expressions that allow us to infer their emotions, there have been few studies on lifelogging techniques that focus upon users’ emotions. In this paper, we develop a system that extracts users’… More >

  • Open AccessOpen Access

    ARTICLE

    Role of Fuzzy Approach towards Fault Detection for Distributed Components

    Yaser Hafeez1, Sadia Ali1, Nz Jhanjhi2, Mamoona Humayun3, Anand Nayyar4,5,*, Mehedi Masud6
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1979-1996, 2021, DOI:10.32604/cmc.2021.014830
    Abstract Component-based software development is rapidly introducing numerous new paradigms and possibilities to deliver highly customized software in a distributed environment. Among other communication, teamwork, and coordination problems in global software development, the detection of faults is seen as the key challenge. Thus, there is a need to ensure the reliability of component-based applications requirements. Distributed device detection faults applied to tracked components from various sources and failed to keep track of all the large number of components from different locations. In this study, we propose an approach for fault detection from component-based systems requirements using… More >

  • Open AccessOpen Access

    REVIEW

    A Comprehensive Review on Medical Diagnosis Using Machine Learning

    Kaustubh Arun Bhavsar1, Ahed Abugabah2, Jimmy Singla1,*, Ahmad Ali AlZubi3, Ali Kashif Bashir4, Nikita5
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1997-2014, 2021, DOI:10.32604/cmc.2021.014943
    (This article belongs to the Special Issue: Machine Learning for Data Analytics)
    Abstract The unavailability of sufficient information for proper diagnosis, incomplete or miscommunication between patient and the clinician, or among the healthcare professionals, delay or incorrect diagnosis, the fatigue of clinician, or even the high diagnostic complexity in limited time can lead to diagnostic errors. Diagnostic errors have adverse effects on the treatment of a patient. Unnecessary treatments increase the medical bills and deteriorate the health of a patient. Such diagnostic errors that harm the patient in various ways could be minimized using machine learning. Machine learning algorithms could be used to diagnose various diseases with high… More >

  • Open AccessOpen Access

    ARTICLE

    Performance of Lung Cancer Prediction Methods Using Different Classification Algorithms

    Yasemin Gültepe*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2015-2028, 2021, DOI:10.32604/cmc.2021.014631
    (This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
    Abstract In 2018, 1.76 million people worldwide died of lung cancer. Most of these deaths are due to late diagnosis, and early-stage diagnosis significantly increases the likelihood of a successful treatment for lung cancer. Machine learning is a branch of artificial intelligence that allows computers to quickly identify patterns within complex and large datasets by learning from existing data. Machine-learning techniques have been improving rapidly and are increasingly used by medical professionals for the successful classification and diagnosis of early-stage disease. They are widely used in cancer diagnosis. In particular, machine learning has been used in… More >

  • Open AccessOpen Access

    ARTICLE

    Modelling the Psychological Impact of COVID-19 in Saudi Arabia Using Machine Learning

    Mohammed A. Aleid1, Khaled A. Z. Alyamani2, Mohieddine Rahmouni2,3, Theyazn H. H. Aldhyani2,*, Nizar Alsharif4, Mohammed Y. Alzahrani4
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2029-2047, 2021, DOI:10.32604/cmc.2021.014873
    (This article belongs to the Special Issue: Application of Big Data Analytics in the Management of Business)
    Abstract This article aims to assess health habits, safety behaviors, and anxiety factors in the community during the novel coronavirus disease (COVID-19) pandemic in Saudi Arabia based on primary data collected through a questionnaire with 320 respondents. In other words, this paper aims to provide empirical insights into the correlation and the correspondence between socio-demographic factors (gender, nationality, age, citizenship factors, income, and education), and psycho-behavioral effects on individuals in response to the emergence of this new pandemic. To focus on the interaction between these variables and their effects, we suggest different methods of analysis, comprising… More >

  • Open AccessOpen Access

    ARTICLE

    Energy Efficient Ambience Awake Routing with OpenFlow Approach

    Hima Bindu Valiveti1,*, SNV Ganesh2, Budati Anil Kumar1, Dileep Kumar Yadav3
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2049-2059, 2021, DOI:10.32604/cmc.2021.014690
    (This article belongs to the Special Issue: Intelligent Communication Systems: Smart Wireless Digital Devices and IoT)
    Abstract A major problem in networking has always been energy consumption. Battery life is one parameter which could help improve Energy Efficiency. Existing research on wireless networking stresses on reducing signaling messages or time required for data transfer for addressing energy consumption issues. Routing or Forwarding packets in a network between the network elements like routers, switches, wireless access points, etc., is complex in conventional networks. With the advent of Software Defined Networking (SDN) for 5G network architectures, the distributed networking has embarked onto centralized networking, wherein the SDN Controller is responsible for decision making. The… More >

  • Open AccessOpen Access

    ARTICLE

    Fractional Rényi Entropy Image Enhancement for Deep Segmentation of Kidney MRI

    Hamid A. Jalab1, Ala’a R. Al-Shamasneh1, Hadil Shaiba2, Rabha W. Ibrahim3,4,*, Dumitru Baleanu5,6,7
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2061-2075, 2021, DOI:10.32604/cmc.2021.015170
    (This article belongs to the Special Issue: Recent Advances in Fractional Calculus Applied to Complex Engineering Phenomena)
    Abstract Recently, many rapid developments in digital medical imaging have made further contributions to health care systems. The segmentation of regions of interest in medical images plays a vital role in assisting doctors with their medical diagnoses. Many factors like image contrast and quality affect the result of image segmentation. Due to that, image contrast remains a challenging problem for image segmentation. This study presents a new image enhancement model based on fractional Rényi entropy for the segmentation of kidney MRI scans. The proposed work consists of two stages: enhancement by fractional Rényi entropy, and MRI… More >

  • Open AccessOpen Access

    ARTICLE

    Coverless Image Steganography Based on Jigsaw Puzzle Image Generation

    Al Hussien Seddik Saad1,*, M. S. Mohamed2,3, E. H. Hafez4
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2077-2091, 2021, DOI:10.32604/cmc.2021.015329
    Abstract Current image steganography methods are working by assigning an image as a cover file then embed the payload within it by modifying its pixels, creating the stego image. However, the left traces that are caused by these modifications will make steganalysis algorithms easily detect the hidden payload. A coverless data hiding concept is proposed to solve this issue. Coverless does not mean that cover is not required, or the payload can be transmitted without a cover. Instead, the payload is embedded by cover generation or a secret message mapping between the cover file and the… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Learning Approach for COVID-19 Detection in Computed Tomography Images

    Mohamad Mahmoud Al Rahhal1, Yakoub Bazi2,*, Rami M. Jomaa3, Mansour Zuair2, Naif Al Ajlan2
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2093-2110, 2021, DOI:10.32604/cmc.2021.014956
    (This article belongs to the Special Issue: Artificial Intelligence and Healthcare Analytics for COVID-19)
    Abstract With the rapid spread of the coronavirus disease 2019 (COVID-19) worldwide, the establishment of an accurate and fast process to diagnose the disease is important. The routine real-time reverse transcription-polymerase chain reaction (rRT-PCR) test that is currently used does not provide such high accuracy or speed in the screening process. Among the good choices for an accurate and fast test to screen COVID-19 are deep learning techniques. In this study, a new convolutional neural network (CNN) framework for COVID-19 detection using computed tomography (CT) images is proposed. The EfficientNet architecture is applied as the backbone… More >

  • Open AccessOpen Access

    ARTICLE

    Modeling the COVID-19 Pandemic Dynamics in Iran and China

    Jin Zhao1, Zubair Ahmad2,*, Zahra Almaspoor2
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2111-2122, 2021, DOI:10.32604/cmc.2021.014259
    (This article belongs to the Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control)
    Abstract The epidemic outbreak COVID-19 was first detected in the Wuhan city of China and then spread worldwide. It is of great interest to the researchers for its high rate of infection spread and its significant number of fatalities. A detailed scientific analysis of this phenomenon is yet to come. However, it is of interest of governments and other responsible institutions to have the right facts and figures to take every possible necessary action such as an arrangement of the appropriate quarantine activities, estimation of the required number of places in hospitals, assessment of the level… More >

  • Open AccessOpen Access

    ARTICLE

    A Machine Learning Approach for Expression Detection in Healthcare Monitoring Systems

    Muhammad Kashif1, Ayyaz Hussain2, Asim Munir1, Abdul Basit Siddiqui3, Aaqif Afzaal Abbasi4, Muhammad Aakif5, Arif Jamal Malik4, Fayez Eid Alazemi6, Oh-Young Song7,*
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2123-2139, 2021, DOI:10.32604/cmc.2021.014782
    Abstract Expression detection plays a vital role to determine the patient’s condition in healthcare systems. It helps the monitoring teams to respond swiftly in case of emergency. Due to the lack of suitable methods, results are often compromised in an unconstrained environment because of pose, scale, occlusion and illumination variations in the image of the face of the patient. A novel patch-based multiple local binary patterns (LBP) feature extraction technique is proposed for analyzing human behavior using facial expression recognition. It consists of three-patch [TPLBP] and four-patch LBPs [FPLBP] based feature engineering respectively. Image representation is… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Learning and Holt-Trend Algorithms for Predicting Covid-19 Pandemic

    Theyazn H. H. Aldhyani1,*, Melfi Alrasheed2, Mosleh Hmoud Al-Adaileh3, Ahmed Abdullah Alqarni4, Mohammed Y. Alzahrani4, Ahmed H. Alahmadi5
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2141-2160, 2021, DOI:10.32604/cmc.2021.014498
    (This article belongs to the Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control)
    Abstract The Covid-19 epidemic poses a serious public health threat to the world, where people with little or no pre-existing human immunity can be more vulnerable to its effects. Thus, developing surveillance systems for predicting the Covid-19 pandemic at an early stage could save millions of lives. In this study, a deep learning algorithm and a Holt-trend model are proposed to predict the coronavirus. The Long-Short Term Memory (LSTM) and Holt-trend algorithms were applied to predict confirmed numbers and death cases. The real time data used has been collected from the World Health Organization (WHO). In… More >

  • Open AccessOpen Access

    ARTICLE

    A Computational Analysis to Burgers Huxley Equation

    Muhammad Saqib1, Muhammad Shoaib Arif2,*, Shahid Hasnain3, Daoud S. Mashat4
    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2161-2183, 2021, DOI:10.32604/cmc.2021.014507
    Abstract The efficiency of solving computationally partial differential equations can be profoundly highlighted by the creation of precise, higher-order compact numerical scheme that results in truly outstanding accuracy at a given cost. The objective of this article is to develop a highly accurate novel algorithm for two dimensional non-linear Burgers Huxley (BH) equations. The proposed compact numerical scheme is found to be free of superiors approximate oscillations across discontinuities, and in a smooth flow region, it efficiently obtained a high-order accuracy. In particular, two classes of higher-order compact finite difference schemes are taken into account and… More >

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