Home / Journals / CMC / Vol.67, No.1, 2021
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  • Open AccessOpen Access

    ARTICLE

    Non-Associative Algebra Redesigning Block Cipher with Color Image Encryption

    Nazli Sanam1,*, Asif Ali1, Tariq Shah1, Ghazanfar Farooq2
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1-21, 2021, DOI:10.32604/cmc.2021.014442
    (This article belongs to the Special Issue: Security and Computing in Internet of Things)
    Abstract The substitution box (S-box) is a fundamentally important component of symmetric key cryptosystem. An S-box is a primary source of non-linearity in modern block ciphers, and it resists the linear attack. Various approaches have been adopted to construct S-boxes. S-boxes are commonly constructed over commutative and associative algebraic structures including Galois fields, unitary commutative rings and cyclic and non-cyclic finite groups. In this paper, first a non-associative ring of order 512 is obtained by using computational techniques, and then by this ring a triplet of 8 × 8 S-boxes is designed. The motivation behind the… More >

  • Open AccessOpen Access

    ARTICLE

    SAPEM: Secure Attestation of Program Execution and Program Memory for IoT Applications

    Nafisa Ahmed1, Manar Abu Talib2,*, Qassim Nasir3
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 23-49, 2021, DOI:10.32604/cmc.2021.014523
    (This article belongs to the Special Issue: Security Issues in Industrial Internet of Things)
    Abstract Security is one of the major challenges that devices connected to the Internet of Things (IoT) face today. Remote attestation is used to measure these devices’ trustworthiness on the network by measuring the device platform’s integrity. Several software-based attestation mechanisms have been proposed, but none of them can detect runtime attacks. Although some researchers have attempted to tackle these attacks, the proposed techniques require additional secured hardware parts to be integrated with the attested devices to achieve their aim. These solutions are expensive and not suitable in many cases. This paper proposes a dual attestation… More >

  • Open AccessOpen Access

    ARTICLE

    A New Multi-Agent Feature Wrapper Machine Learning Approach for Heart Disease Diagnosis

    Mohamed Elhoseny1, Mazin Abed Mohammed2,*, Salama A. Mostafa3, Karrar Hameed Abdulkareem4, Mashael S. Maashi5, Begonya Garcia-Zapirain6, Ammar Awad Mutlag7, Marwah Suliman Maashi8
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 51-71, 2021, DOI:10.32604/cmc.2021.012632
    (This article belongs to the Special Issue: Deep Learning Trends in Intelligent Systems)
    Abstract Heart disease (HD) is a serious widespread life-threatening disease. The heart of patients with HD fails to pump sufficient amounts of blood to the entire body. Diagnosing the occurrence of HD early and efficiently may prevent the manifestation of the debilitating effects of this disease and aid in its effective treatment. Classical methods for diagnosing HD are sometimes unreliable and insufficient in analyzing the related symptoms. As an alternative, noninvasive medical procedures based on machine learning (ML) methods provide reliable HD diagnosis and efficient prediction of HD conditions. However, the existing models of automated ML-based… More >

  • Open AccessOpen Access

    ARTICLE

    Application of Metaheuristic Algorithms for Optimizing Longitudinal Square Porous Fins

    Samer H. Atawneh1, Waqar A. Khan2, Nawaf N. Hamadneh3,*, Adeeb M. Alhomoud3
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 73-87, 2021, DOI:10.32604/cmc.2021.012351
    Abstract The objectives of this study involve the optimization of longitudinal porous fins of square cross-section using metaheuristic algorithms. A generalized nonlinear ordinary differential equation is derived using Darcy and Fourier’s laws in the energy balance around a control volume and is solved numerically using RFK 45 method. The temperature of the base surface is higher than the fin surface, and the fin tip is kept adiabatic or cooled by convection heat transfer. The other pertinent parameters include Rayleigh number (100 ≤ Ra ≤ 104), Darcy number, (10−4 ≤ Da ≤ 10−2), relative thermal conductivity ratio of solid phase to fluid (1000 ≤ kr ≤ 8000), Nusselt number (10 ≤ Nu ≤ 100), More >

  • Open AccessOpen Access

    REVIEW

    Osteoporosis Prediction for Trabecular Bone using Machine Learning: A Review

    Marrium Anam1, Vasaki a/p Ponnusamy2,*, Muzammil Hussain3, Muhammad Waqas Nadeem2,4, Mazhar Javed3, Hock Guan Goh2, Sadia Qadeer3
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 89-105, 2021, DOI:10.32604/cmc.2021.013159
    Abstract Trabecular bone holds the utmost importance due to its significance regarding early bone loss. Diseases like osteoporosis greatly affect the structure of the Trabecular bone which results in different outcomes like high risk of fracture. The objective of this paper is to inspect the characteristics of the Trabecular Bone by using the Magnetic Resonance Imaging (MRI) technique. These characteristics prove to be quite helpful in studying different studies related to Trabecular bone such as osteoporosis. The things that were considered before the selection of the articles for the systematic review were language, research field, and… More >

  • Open AccessOpen Access

    REVIEW

    Medical Diagnosis Using Machine Learning: A Statistical Review

    Kaustubh Arun Bhavsar1, Jimmy Singla1, Yasser D. Al-Otaibi2, Oh-Young Song3,*, Yousaf Bin Zikria4, Ali Kashif Bashir5
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 107-125, 2021, DOI:10.32604/cmc.2021.014604
    (This article belongs to the Special Issue: Intelligent Decision Support Systems for Complex Healthcare Applications)
    Abstract Decision making in case of medical diagnosis is a complicated process. A large number of overlapping structures and cases, and distractions, tiredness, and limitations with the human visual system can lead to inappropriate diagnosis. Machine learning (ML) methods have been employed to assist clinicians in overcoming these limitations and in making informed and correct decisions in disease diagnosis. Many academic papers involving the use of machine learning for disease diagnosis have been increasingly getting published. Hence, to determine the use of ML to improve the diagnosis in varied medical disciplines, a systematic review is conducted… More >

  • Open AccessOpen Access

    ARTICLE

    Soil Properties for Earthen Building Construction in Najran City, Saudi Arabia

    Yaser Khaled Al-Sakkaf1, Gamil M. S. Abdullah2,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 127-140, 2021, DOI:10.32604/cmc.2021.014438
    (This article belongs to the Special Issue: Wireless Sensors Networks Application in Healthcare and Medical Internet of Things (Miot) in Bio-Medical Sensors Networks)
    Abstract Earth is the most common and important building material used in the construction industry, since it is found in almost every country in the world. Modern earthen construction is alive and well, and is spread over an enormous geographical area. This technique utilizes various earthen materials and numerous methods, and features many benefits for both construction in general and buildings in particular. Najran, a city located in the south of Saudi Arabia, is distinguished by its heritage of earthen architecture, which displays many advantages and a marvelous variety of types and exterior designs. Many weaknesses… More >

  • Open AccessOpen Access

    ARTICLE

    A Blockchain Based Framework for Stomach Abnormalities Recognition

    Muhammad Attique Khan1, Inzamam Mashood Nasir1, Muhammad Sharif2, Majed Alhaisoni3, Seifedine Kadry4, Syed Ahmad Chan Bukhari5, Yunyoung Nam6,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 141-158, 2021, DOI:10.32604/cmc.2021.013217
    (This article belongs to the Special Issue: Innovation of Blockchain Technology)
    Abstract Wireless Capsule Endoscopy (WCE) is an imaging technology, widely used in medical imaging for stomach infection recognition. However, a one patient procedure takes almost seven to eight minutes and approximately 57,000 frames are captured. The privacy of patients is very important and manual inspection is time consuming and costly. Therefore, an automated system for recognition of stomach infections from WCE frames is always needed. An existing block chain-based approach is employed in a convolutional neural network model to secure the network for accurate recognition of stomach infections such as ulcer and bleeding. Initially, images are… More >

  • Open AccessOpen Access

    ARTICLE

    Technology Provides Better Document Search Results on Slovak Legislation Webpage as Result of a Simulation of Webpage Performance Parameters

    Peter Kvasnica*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 159-170, 2021, DOI:10.32604/cmc.2021.013587
    Abstract This article acquaints the public with the insights gained from conducting document searches in the Slovak public administration information system, when supported by knowledge of its management. Additionally, it discusses the advantages of simulating performance parameters and comparing the obtained results with the real parameters of the eZbierka (eCollection) legislation webpage. This comparison was based upon simulated results, obtained through the Gatling simulation tool, versus those obtained from measuring the properties of the public administration legislation webpage. Both sets of data (simulated and real), were generated via the the document search technologies in place on… More >

  • Open AccessOpen Access

    ARTICLE

    A Weighted Spatially Constrained Finite Mixture Model for Image Segmentation

    Mohammad Masroor Ahmed1,*, Saleh Al Shehri2, Jawad Usman Arshed3, Mahmood Ul Hassan4, Muzammil Hussain5, Mehtab Afzal6
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 171-185, 2021, DOI:10.32604/cmc.2021.014141
    Abstract Spatially Constrained Mixture Model (SCMM) is an image segmentation model that works over the framework of maximum a-posteriori and Markov Random Field (MAP-MRF). It developed its own maximization step to be used within this framework. This research has proposed an improvement in the SCMM’s maximization step for segmenting simulated brain Magnetic Resonance Images (MRIs). The improved model is named as the Weighted Spatially Constrained Finite Mixture Model (WSCFMM). To compare the performance of SCMM and WSCFMM, simulated T1-Weighted normal MRIs were segmented. A region of interest (ROI) was extracted from segmented images. The similarity level More >

  • Open AccessOpen Access

    ARTICLE

    Estimating Security Risk of Healthcare Web Applications: A Design Perspective

    Fahad A. Alzahrani*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 187-209, 2021, DOI:10.32604/cmc.2021.014007
    Abstract In the recent years, the booming web-based applications have attracted the hackers’ community. The security risk of the web-based hospital management system (WBHMS) has been increasing rapidly. In the given context, the main goal of all security professionals and website developers is to maintain security divisions and improve on the user’s confidence and satisfaction. At this point, the different WBHMS tackle different types of security risks. In WBHMS, the security of the patients’ medical information is of utmost importance. All in all, there is an inherent security risk of data and assets in the field… More >

  • Open AccessOpen Access

    ARTICLE

    Blockchain-Enabled EHR Framework for Internet of Medical Things

    Lewis Nkenyereye1,*, S. M. Riazul Islam2, Mahmud Hossain3, M. Abdullah-Al-Wadud4, Atif Alamri4
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 211-221, 2021, DOI:10.32604/cmc.2021.013796
    (This article belongs to the Special Issue: Intelligent Decision Support Systems for Complex Healthcare Applications)
    Abstract The Internet of Medical Things (IoMT) offers an infrastructure made of smart medical equipment and software applications for healthcare services. Through the internet, the IoMT is capable of providing remote medical diagnosis and timely health services. The patients can use their smart devices to create, store and share their electronic health records (EHR) with a variety of medical personnel including medical doctors and nurses. However, unless the underlying commination within IoMT is secured, malicious users can intercept, modify and even delete the sensitive EHR data of patients. Patients also lose full control of their EHR… More >

  • Open AccessOpen Access

    ARTICLE

    A Secure NDN Framework for Internet of Things Enabled Healthcare

    Syed Sajid Ullah1, Saddam Hussain1,*, Abdu Gumaei2,3, Hussain AlSalman2,4
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 223-240, 2021, DOI:10.32604/cmc.2021.014413
    (This article belongs to the Special Issue: Security and Computing in Internet of Things)
    Abstract Healthcare is a binding domain for the Internet of Things (IoT) to automate healthcare services for sharing and accumulation patient records at anytime from anywhere through the Internet. The current IP-based Internet architecture suffers from latency, mobility, location dependency, and security. The Named Data Networking (NDN) has been projected as a future internet architecture to cope with the limitations of IP-based Internet. However, the NDN infrastructure does not have a secure framework for IoT healthcare information. In this paper, we proposed a secure NDN framework for IoT-enabled Healthcare (IoTEH). In the proposed work, we adopt… More >

  • Open AccessOpen Access

    ARTICLE

    A Phase Estimation Algorithm for Quantum Speed-Up Multi-Party Computing

    Wenbin Yu1, Hao Feng1, Yinsong Xu1, Na Yin1, Yadang Chen2,3, Zhi-Xin Yang3,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 241-252, 2021, DOI:10.32604/cmc.2021.012649
    Abstract Security and privacy issues have attracted the attention of researchers in the field of IoT as the information processing scale grows in sensor networks. Quantum computing, theoretically known as an absolutely secure way to store and transmit information as well as a speed-up way to accelerate local or distributed classical algorithms that are hard to solve with polynomial complexity in computation or communication. In this paper, we focus on the phase estimation method that is crucial to the realization of a general multi-party computing model, which is able to be accelerated by quantum algorithms. A More >

  • Open AccessOpen Access

    ARTICLE

    Optimal Resource Allocation and Quality of Service Prediction in Cloud

    Priya Baldoss1,2,*, Gnanasekaran Thangavel3
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 253-265, 2021, DOI:10.32604/cmc.2021.013695
    Abstract In the present scenario, cloud computing service provides on-request access to a collection of resources available in remote system that can be shared by numerous clients. Resources are in self-administration; consequently, clients can adjust their usage according to their requirements. Resource usage is estimated and clients can pay according to their utilization. In literature, the existing method describes the usage of various hardware assets. Quality of Service (QoS) needs to be considered for ascertaining the schedule and the access of resources. Adhering with the security arrangement, any additional code is forbidden to ensure the usage… More >

  • Open AccessOpen Access

    ARTICLE

    A Fast and Effective Multiple Kernel Clustering Method on Incomplete Data

    Lingyun Xiang1,2, Guohan Zhao1, Qian Li3, Gwang-Jun Kim4,*, Osama Alfarraj5, Amr Tolba5,6
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 267-284, 2021, DOI:10.32604/cmc.2021.013488
    Abstract Multiple kernel clustering is an unsupervised data analysis method that has been used in various scenarios where data is easy to be collected but hard to be labeled. However, multiple kernel clustering for incomplete data is a critical yet challenging task. Although the existing absent multiple kernel clustering methods have achieved remarkable performance on this task, they may fail when data has a high value-missing rate, and they may easily fall into a local optimum. To address these problems, in this paper, we propose an absent multiple kernel clustering (AMKC) method on incomplete data. The… More >

  • Open AccessOpen Access

    ARTICLE

    Acceptance Sampling Plans with Truncated Life Tests for the Length-Biased Weighted Lomax Distribution

    Amer Ibrahim Al-Omari1,*, Ibrahim M. Almanjahie2,3, Olena Kravchuk4
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 285-301, 2021, DOI:10.32604/cmc.2021.014537
    (This article belongs to the Special Issue: Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
    Abstract In this paper, we considered the Length-biased weighted Lomax distribution and constructed new acceptance sampling plans (ASPs) where the life test is assumed to be truncated at a pre-assigned time. For the new suggested ASPs, the tables of the minimum samples sizes needed to assert a specific mean life of the test units are obtained. In addition, the values of the corresponding operating characteristic function and the associated producer’s risks are calculated. Analyses of two real data sets are presented to investigate the applicability of the proposed acceptance sampling plans; one data set contains the More >

  • Open AccessOpen Access

    ARTICLE

    On Computing the Suitability of Non-Human Resources for Business Process Analysis

    Abid Sohail1,*, Khurram Shahzad2, P. D. D. Dominic3, Muhammad Arif Butt2, Muhammad Arif4, Muhammad Imran Tariq5
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 303-319, 2021, DOI:10.32604/cmc.2021.014201
    (This article belongs to the Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
    Abstract Business process improvement is a systematic approach used by several organizations to continuously improve their quality of service. Integral to that is analyzing the current performance of each task of the process and assigning the most appropriate resources to each task. In continuation of our previous work, we categorize resources into human and non-human resources. For instance, in the healthcare domain, human resources include doctors, nurses, and other associated staff responsible for the execution of healthcare activities; whereas the non-human resources include surgical and other equipment needed for execution. In this study, we contend that… More >

  • Open AccessOpen Access

    ARTICLE

    A Bio-Inspired Routing Optimization in UAV-enabled Internet of Everything

    Masood Ahmad1, Fasee Ullah2,*, Ishtiaq Wahid1, Atif Khan3, M. Irfan Uddin4, Abdullah Alharbi5, Wael Alosaimi5
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 321-336, 2021, DOI:10.32604/cmc.2021.014102
    (This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
    Abstract Internet of Everything (IoE) indicates a fantastic vision of the future, where everything is connected to the internet, providing intelligent services and facilitating decision making. IoE is the collection of static and moving objects able to coordinate and communicate with each other. The moving objects may consist of ground segments and flying segments. The speed of flying segment e.g., Unmanned Ariel Vehicles (UAVs) may high as compared to ground segment objects. The topology changes occur very frequently due to high speed nature of objects in UAV-enabled IoE (Ue-IoE). The routing maintenance overhead may increase when… More >

  • Open AccessOpen Access

    ARTICLE

    An AIoT Monitoring System for Multi-Object Tracking and Alerting

    Wonseok Jung1, Se-Han Kim2, Seng-Phil Hong3, Jeongwook Seo4,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 337-348, 2021, DOI:10.32604/cmc.2021.014561
    (This article belongs to the Special Issue: Artificial Intelligence based Smart precision agriculture with analytic pattern in sustainable environments using IoT)
    Abstract Pig farmers want to have an effective solution for automatically detecting and tracking multiple pigs and alerting their conditions in order to recognize disease risk factors quickly. In this paper, therefore, we propose a novel monitoring system using an Artificial Intelligence of Things (AIoT) technique combining artificial intelligence and Internet of Things (IoT). The proposed system consists of AIoT edge devices and a central monitoring server. First, an AIoT edge device extracts video frame images from a CCTV camera installed in a pig pen by a frame extraction method, detects multiple pigs in the images More >

  • Open AccessOpen Access

    ARTICLE

    Detection Technique of Software-Induced Rowhammer Attacks

    Minkyung Lee1, Jin Kwak2,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 349-367, 2021, DOI:10.32604/cmc.2021.014700
    Abstract Side-channel attacks have recently progressed into software-induced attacks. In particular, a rowhammer attack, which exploits the characteristics of dynamic random access memory (DRAM), can quickly and continuously access the cells as the cell density of DRAM increases, thereby generating a disturbance error affecting the neighboring cells, resulting in bit flips. Although a rowhammer attack is a highly sophisticated attack in which disturbance errors are deliberately generated into data bits, it has been reported that it can be exploited on various platforms such as mobile devices, web browsers, and virtual machines. Furthermore, there have been studies… More >

  • Open AccessOpen Access

    ARTICLE

    Information Theoretic Weighted Fuzzy Clustering Ensemble

    Yixuan Wang1, Liping Yuan2,3, Harish Garg4, Ali Bagherinia5, Parvïn Hamïd6,7,8,*, Kim-Hung Pho9, Zulkefli Mansor10
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 369-392, 2021, DOI:10.32604/cmc.2021.012850
    Abstract In order to improve performance and robustness of clustering, it is proposed to generate and aggregate a number of primary clusters via clustering ensemble technique. Fuzzy clustering ensemble approaches attempt to improve the performance of fuzzy clustering tasks. However, in these approaches, cluster (or clustering) reliability has not paid much attention to. Ignoring cluster (or clustering) reliability makes these approaches weak in dealing with low-quality base clustering methods. In this paper, we have utilized cluster unreliability estimation and local weighting strategy to propose a new fuzzy clustering ensemble method which has introduced Reliability Based weighted… More >

  • Open AccessOpen Access

    ARTICLE

    Timing and Classification of Patellofemoral Osteoarthritis Patients Using Fast Large Margin Classifier

    Mai Ramadan Ibraheem1, Jilan Adel2, Alaa Eldin Balbaa3, Shaker El-Sappagh4, Tamer Abuhmed5,*, Mohammed Elmogy6
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 393-409, 2021, DOI:10.32604/cmc.2021.014446
    (This article belongs to the Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
    Abstract Surface electromyogram (sEMG) processing and classification can assist neurophysiological standardization and evaluation and provide habitational detection. The timing of muscle activation is critical in determining various medical conditions when looking at sEMG signals. Understanding muscle activation timing allows identification of muscle locations and feature validation for precise modeling. This work aims to develop a predictive model to investigate and interpret Patellofemoral (PF) osteoarthritis based on features extracted from the sEMG signal using pattern classification. To this end, sEMG signals were acquired from five core muscles over about 200 reads from healthy adult patients while they… More >

  • Open AccessOpen Access

    ARTICLE

    Classification of Fundus Images Based on Deep Learning for Detecting Eye Diseases

    Nakhim Chea1, Yunyoung Nam2,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 411-426, 2021, DOI:10.32604/cmc.2021.013390
    (This article belongs to the Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
    Abstract Various techniques to diagnose eye diseases such as diabetic retinopathy (DR), glaucoma (GLC), and age-related macular degeneration (AMD), are possible through deep learning algorithms. A few recent studies have examined a couple of major diseases and compared them with data from healthy subjects. However, multiple major eye diseases, such as DR, GLC, and AMD, could not be detected simultaneously by computer-aided systems to date. There were just high-performance-outcome researches on a pair of healthy and eye-diseased group, besides of four categories of fundus image classification. To have a better knowledge of multi-categorical classification of fundus… More >

  • Open AccessOpen Access

    ARTICLE

    Cardiac Arrhythmia Disease Classification Using LSTM Deep Learning Approach

    Muhammad Ashfaq Khan, Yangwoo Kim*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 427-443, 2021, DOI:10.32604/cmc.2021.014682
    (This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
    Abstract Many approaches have been tried for the classification of arrhythmia. Due to the dynamic nature of electrocardiogram (ECG) signals, it is challenging to use traditional handcrafted techniques, making a machine learning (ML) implementation attractive. Competent monitoring of cardiac arrhythmia patients can save lives. Cardiac arrhythmia prediction and classification has improved significantly during the last few years. Arrhythmias are a group of conditions in which the electrical activity of the heart is abnormal, either faster or slower than normal. It is the most frequent cause of death for both men and women every year in the… More >

  • Open AccessOpen Access

    ARTICLE

    Computation Analysis of Brand Experience Dimensions: Indian Online Food Delivery Platforms

    Sufyan Habib1, Nawaf N. Hamadneh2,*, S. Al wadi3, Ra’ed Masa’deh4
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 445-462, 2021, DOI:10.32604/cmc.2021.014047
    (This article belongs to the Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control)
    Abstract Online Food Delivery Platforms (OFDPs) has witnessed phenomenal growth in the past few years, especially this year due to the COVID-19 pandemic. This Pandemic has forced many governments across the world to give momentum to OFD services and make their presence among the customers. The Presence of several multinational and national companies in this sector has enhanced the competition and companies are trying to adapt various marketing strategies and exploring the brand experience (BEX) dimension that helps in enhancing the brand equity (BE) of OFDPs. BEXs are critical for building brand loyalty (BL) and making… More >

  • Open AccessOpen Access

    ARTICLE

    Efficient UAV Communications: Recent Trends and Challenges

    Abdulfattah Noorwali1, Muhammad Awais Javed2, Mohammad Zubair Khan3,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 463-476, 2021, DOI:10.32604/cmc.2021.014668
    Abstract Unmanned Ariel Vehicles (UAVs) are flying objects whose trajectory can be remotely controlled. UAVs have lot of potential applications in the areas of wireless communications, internet of things, security, traffic management, monitoring, and smart surveying. By enabling reliable communication between UAVs and ground nodes, emergency notifications can be efficiently and quickly disseminated to a wider area. UAVs can gather data from remote areas, industrial units, and emergency scenarios without human involvement. UAVs can support ubiquitous connectivity, green communications, and intelligent wireless resource management. To efficiently use UAVs for all these applications, important challenges need to… More >

  • Open AccessOpen Access

    ARTICLE

    Novel Analytical Thermal Performance Rate Analysis in ZnO-SAE50 Nanolubricant: Nonlinear Mathematical Model

    Adnan1, Umar Khan2, Naveed Ahmed3, Syed Tauseef Mohyud-Din4, Ilyas Khan5,*, El-Sayed M. Sherif6,7
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 477-489, 2021, DOI:10.32604/cmc.2021.012739
    Abstract The investigation of local thermal transport rate in the nanolubricants is significant. These lubricants are broadly used in environmental pollution, mechanical engineering and in the paint industry due to high thermal performance rate. Therefore, thermal transport in ZnO-SAE50 nanolubricant under the impacts of heat generation/absorption is conducted. The colloidal suspension is flowing between parallel stretching disks in which the lower disk is positioned at z = 0 and upper disk apart from distance d. The problem is transformed in dimensionless version via described similarity transforms. In the next stage, an analytical technique (VPM) is implemented for… More >

  • Open AccessOpen Access

    ARTICLE

    Accurate Fault Location Modeling for Parallel Transmission Lines Considering Mutual Effect

    Hamdy A. Ziedan1, Hegazy Rezk2,3, Mujahed Al-Dhaifallah4,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 491-518, 2021, DOI:10.32604/cmc.2021.014493
    (This article belongs to the Special Issue: Interval Arithmetic with Applications to Physical Phenomena)
    Abstract A new accurate algorithms based on mathematical modeling of two parallel transmissions lines system (TPTLS) as influenced by the mutual effect to determine the fault location is discussed in this work. The distance relay measures the impedance to the fault location which is the positive-sequence. The principle of summation the positive-, negative-, and zero-sequence voltages which equal zero is used to determine the fault location on the TPTLS. Also, the impedance of the transmission line to the fault location is determined. These algorithms are applied to single-line-to-ground (SLG) and double-line-to-ground (DLG) faults. To detect the More >

  • Open AccessOpen Access

    ARTICLE

    Intelligent Cloud Based Load Balancing System Empowered with Fuzzy Logic

    Atif Ishaq Khan1, Syed Asad Raza Kazmi1, Ayesha Atta1,*, Muhammad Faheem Mushtaq2, Muhammad Idrees3, Ilyas Fakir1, Muhammad Safyan1, Muhammad Adnan Khan4, Awais Qasim1
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 519-528, 2021, DOI:10.32604/cmc.2021.013865
    (This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
    Abstract Cloud computing is seeking attention as a new computing paradigm to handle operations more efficiently and cost-effectively. Cloud computing uses dynamic resource provisioning and de-provisioning in a virtualized environment. The load on the cloud data centers is growing day by day due to the rapid growth in cloud computing demand. Elasticity in cloud computing is one of the fundamental properties, and elastic load balancing automatically distributes incoming load to multiple virtual machines. This work is aimed to introduce efficient resource provisioning and de-provisioning for better load balancing. In this article, a model is proposed in More >

  • Open AccessOpen Access

    ARTICLE

    Suitability of VVC and HEVC for Video Telehealth Systems

    Muhammad Arslan Usman1,4,*, Muhammad Rehan Usman2, Rizwan Ali Naqvi3, Bernie Mcphilips4, Christopher Romeika4, Daniel Cunliffe4, Christos Politis1, Nada Philip1
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 529-547, 2021, DOI:10.32604/cmc.2021.014614
    Abstract Video compression in medical video streaming is one of the key technologies associated with mobile healthcare. Seamless delivery of medical video streams over a resource constrained network emphasizes the need of a video codec that requires minimum bitrates and maintains high perceptual quality. This paper presents a comparative study between High Efficiency Video Coding (HEVC) and its potential successor Versatile Video Coding (VVC) in the context of healthcare. A large-scale subjective experiment comprising of twenty-four non-expert participants is presented for eight different test conditions in Full High Definition (FHD) videos. The presented analysis highlights the… More >

  • Open AccessOpen Access

    ARTICLE

    Tele-COVID: A Telemedicine SOA-Based Architectural Design for COVID-19 Patients

    Asadullah Shaikh*, Mana Saleh AlReshan, Yousef Asiri, Adel Sulaiman, Hani Alshahrani
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 549-576, 2021, DOI:10.32604/cmc.2021.014813
    (This article belongs to the Special Issue: COVID-19 impacts on Software Engineering industry and research community)
    Abstract In Wuhan, China, a novel Corona Virus (COVID-19) was detected in December 2019; it has changed the entire world and to date, the number of diagnosed cases is 38,756,2891 and 1,095,2161 people have died. This happened because a large number of people got affected and there is a lack of hospitals for COVID-19 patients. One of the precautionary measures for COVID-19 patients is isolation. To support this, there is an urgent need for a platform that makes treatment possible from a distance. Telemedicine systems have been drastically increasing in number and size over recent years. This More >

  • Open AccessOpen Access

    ARTICLE

    The Interaction between Microcapsules with Different Sizes and Propagating Cracks

    Xiaoying Zhuang2,3, Hung Nguyen-Xuan4,5, Shuai Zhou1,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 577-593, 2021, DOI:10.32604/cmc.2021.014688
    Abstract The microcapsule-contained self-healing materials are appealing since they can heal the cracks automatically and be effective for a long time. Although many experiments have been carried out, the influence of the size of microcapsules on the self-healing effect is still not well investigated. This study uses the two-dimensional discrete element method (DEM) to investigate the interaction between one microcapsule and one microcrack. The influence of the size of microcapsules is considered. The potential healing time and the influence of the initial damage are studied. The results indicate that the coalescence crack is affected by the More >

  • Open AccessOpen Access

    ARTICLE

    Image-Based Automatic Diagnostic System for Tomato Plants Using Deep Learning

    Shaheen Khatoon1,*, Md Maruf Hasan1, Amna Asif1, Majed Alshmari1, Yun-Kiam Yap2
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 595-612, 2021, DOI:10.32604/cmc.2021.014580
    (This article belongs to the Special Issue: Deep Learning Trends in Intelligent Systems)
    Abstract Tomato production is affected by various threats, including pests, pathogens, and nutritional deficiencies during its growth process. If control is not timely, these threats affect the plant-growth, fruit-yield, or even loss of the entire crop, which is a key danger to farmers’ livelihood and food security. Traditional plant disease diagnosis methods heavily rely on plant pathologists that incur high processing time and huge cost. Rapid and cost-effective methods are essential for timely detection and early intervention of basic food threats to ensure food security and reduce substantial economic loss. Recent developments in Artificial Intelligence (AI)… More >

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    ARTICLE

    Intelligent Fusion of Infrared and Visible Image Data Based on Convolutional Sparse Representation and Improved Pulse-Coupled Neural Network

    Jingming Xia1, Yi Lu1, Ling Tan2,*, Ping Jiang3
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 613-624, 2021, DOI:10.32604/cmc.2021.013457
    Abstract Multi-source information can be obtained through the fusion of infrared images and visible light images, which have the characteristics of complementary information. However, the existing acquisition methods of fusion images have disadvantages such as blurred edges, low contrast, and loss of details. Based on convolution sparse representation and improved pulse-coupled neural network this paper proposes an image fusion algorithm that decompose the source images into high-frequency and low-frequency subbands by non-subsampled Shearlet Transform (NSST). Furthermore, the low-frequency subbands were fused by convolutional sparse representation (CSR), and the high-frequency subbands were fused by an improved pulse More >

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    ARTICLE

    Security Requirement Management for Cloud-Assisted and Internet of Things—Enabled Smart City

    Muhammad Usman Tariq1, Muhammad Babar2, Mian Ahmad Jan3,4,5,*, Akmal Saeed Khattak6, Mohammad Dahman Alshehri7, Abid Yahya8
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 625-639, 2021, DOI:10.32604/cmc.2021.014165
    (This article belongs to the Special Issue: Machine Learning-based Secured and Privacy-preserved Smart City)
    Abstract The world is rapidly changing with the advance of information technology. The expansion of the Internet of Things (IoT) is a huge step in the development of the smart city. The IoT consists of connected devices that transfer information. The IoT architecture permits on-demand services to a public pool of resources. Cloud computing plays a vital role in developing IoT-enabled smart applications. The integration of cloud computing enhances the offering of distributed resources in the smart city. Improper management of security requirements of cloud-assisted IoT systems can bring about risks to availability, security, performance, confidentiality, More >

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    ARTICLE

    Machine Learning Enabled Early Detection of Breast Cancer by Structural Analysis of Mammograms

    Mavra Mehmood1, Ember Ayub1, Fahad Ahmad1,6,*, Madallah Alruwaili2, Ziyad A. Alrowaili3, Saad Alanazi2, Mamoona Humayun2, Muhammad Rizwan1, Shahid Naseem4, Tahir Alyas5
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 641-657, 2021, DOI:10.32604/cmc.2021.013774
    (This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
    Abstract Clinical image processing plays a significant role in healthcare systems and is currently a widely used methodology. In carcinogenic diseases, time is crucial; thus, an image’s accurate analysis can help treat disease at an early stage. Ductal carcinoma in situ (DCIS) and lobular carcinoma in situ (LCIS) are common types of malignancies that affect both women and men. The number of cases of DCIS and LCIS has increased every year since 2002, while it still takes a considerable amount of time to recommend a controlling technique. Image processing is a powerful technique to analyze preprocessed… More >

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    ARTICLE

    Hacking Anti-Shoplifting System to Hide Data within Clothes

    Al Hussien Seddik Saad1,*, E. H. Hafez2, Zubair Ahmad3
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 659-674, 2021, DOI:10.32604/cmc.2021.014758
    Abstract Steganography has been used to prevent unauthorized access to private information during transmission. It is the scheme of securing sensitive information by concealing it within carriers such as digital images, videos, audio, or text. Current steganography methods are working by assigning a cover file then embed the payload within it by making some modifications, creating the stego-file. However, the left traces that are caused by these modifications will make steganalysis algorithms easily detect the hidden payload. Aiming to solve this issue, a novel, highly robust steganography method based on hacking anti-shoplifting systems has proposed to… More >

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    ARTICLE

    Dynamical Behaviors of Nonlinear Coronavirus (COVID-19) Model with Numerical Studies

    Khaled A. Gepreel1,2, Mohamed S. Mohamed1,3, Hammad Alotaibi1, Amr M. S. Mahdy1,2,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 675-686, 2021, DOI:10.32604/cmc.2021.012200
    (This article belongs to the Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control)
    Abstract The development of mathematical modeling of infectious diseases is a key research area in various fields including ecology and epidemiology. One aim of these models is to understand the dynamics of behavior in infectious diseases. For the new strain of coronavirus (COVID-19), there is no vaccine to protect people and to prevent its spread so far. Instead, control strategies associated with health care, such as social distancing, quarantine, travel restrictions, can be adopted to control the pandemic of COVID-19. This article sheds light on the dynamical behaviors of nonlinear COVID-19 models based on two methods: More >

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    ARTICLE

    Survey of Robotics in Education, Taxonomy, Applications, and Platforms during COVID-19

    Hussain A. Younis1,2, A. S. A. Mohamed2,*, R. Jamaludin3, M. N. Ab Wahab2
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 687-707, 2021, DOI:10.32604/cmc.2021.013746
    (This article belongs to the Special Issue: Big Data, Analytics and Intelligent Algorithms for COVID-19)
    Abstract The coronavirus disease 2019 (COVID-19) is characterized as a disease caused by a novel coronavirus known as severe acute respiratory coronavirus syndrome 2 (SARS-CoV-2; formerly known as 2019-nCoV). In December 2019, COVID-19 began to appear in a few countries. By the beginning of 2020, it had spread to most countries across the world. This is when education challenges began to arise. The COVID-19 crisis led to the closure of thousands of schools and universities all over the world. Such a situation requires reliance on e-learning and robotics education for students to continue their studies to… More >

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    ARTICLE

    Automatic Segmentation of Liver from Abdominal Computed Tomography Images Using Energy Feature

    Prabakaran Rajamanickam1, Shiloah Elizabeth Darmanayagam1,*, Sunil Retmin Raj Cyril Raj2
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 709-722, 2021, DOI:10.32604/cmc.2021.014347
    Abstract Liver Segmentation is one of the challenging tasks in detecting and classifying liver tumors from Computed Tomography (CT) images. The segmentation of hepatic organ is more intricate task, owing to the fact that it possesses a sizeable quantum of vascularization. This paper proposes an algorithm for automatic seed point selection using energy feature for use in level set algorithm for segmentation of liver region in CT scans. The effectiveness of the method can be determined when used in a model to classify the liver CT images as tumorous or not. This involves segmentation of the… More >

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    ARTICLE

    An Efficient Sound and Data Steganography Based Secure Authentication System

    Debajit Datta1, Lalit Garg2,*, Kathiravan Srinivasan3, Atsushi Inoue4, G. Thippa Reddy3, M. Praveen Kumar Reddy3, K. Ramesh5, Nidal Nasser6
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 723-751, 2021, DOI:10.32604/cmc.2021.014802
    (This article belongs to the Special Issue: Artificial Intelligence and Big Data in Entrepreneurship)
    Abstract The prodigious advancements in contemporary technologies have also brought in the situation of unprecedented cyber-attacks. Further, the pin-based security system is an inadequate mechanism for handling such a scenario. The reason is that hackers use multiple strategies for evading security systems and thereby gaining access to private data. This research proposes to deploy diverse approaches for authenticating and securing a connection amongst two devices/gadgets via sound, thereby disregarding the pins’ manual verification. Further, the results demonstrate that the proposed approaches outperform conventional pin-based authentication or QR authentication approaches. Firstly, a random signal is encrypted, and… More >

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    ARTICLE

    On the Genesis of the Marshall-Olkin Family of Distributions via the T-X Family Approach: Statistical Modeling

    Yang Zhenwu1, Zubair Ahmad2,*, Zahra Almaspoor2, Saima K. Khosa3
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 753-760, 2021, DOI:10.32604/cmc.2021.012393
    Abstract In the last couple of years, there Has been an increased interest among the statisticians to define new families of distributions by adding one or more additional parameter(s) to the baseline distribution. In this regard, a number of families have been introduced and studied. One such example is the Marshall-Olkin family of distributions that is one of the most prominent approaches used to generalize the existing distributions. Whenever, we see a new method, the natural questions come in to mind are (i) what are the genesis of the newly proposed method and (ii) how did… More >

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    ARTICLE

    Epithelial Layer Estimation Using Curvatures and Textural Features for Dysplastic Tissue Detection

    Afzan Adam1,*, Abdul Hadi Abd Rahman1, Nor Samsiah Sani1, Zaid Abdi Alkareem Alyessari1, Nur Jumaadzan Zaleha Mamat2, Basela Hasan3
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 761-777, 2021, DOI:10.32604/cmc.2021.014599
    (This article belongs to the Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
    Abstract Boundary effect in digital pathology is a phenomenon where the tissue shapes of biopsy samples get distorted during the sampling process. The morphological pattern of an epithelial layer is greatly affected. Theoretically, the shape deformation model can normalise the distortions, but it needs a 2D image. Curvatures theory, on the other hand, is not yet tested on digital pathology images. Therefore, this work proposed a curvature detection to reduce the boundary effects and estimates the epithelial layer. The boundary effect on the tissue surfaces is normalised using the frequency of a curve deviates from being… More >

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    ARTICLE

    Secure Cloud Data Storage System Using Hybrid Paillier–Blowfish Algorithm

    Bijeta Seth1, Surjeet Dalal1, Dac-Nhuong Le2,3,*, Vivek Jaglan4, Neeraj Dahiya1, Akshat Agrawal5, Mayank Mohan Sharma6, Deo Prakash7, K. D. Verma8
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 779-798, 2021, DOI:10.32604/cmc.2021.014466
    Abstract Cloud computing utilizes enormous clusters of serviceable and manageable resources that can be virtually and dynamically reconfigured in order to deliver optimum resource utilization by exploiting the pay-per-use model. However, concerns around security have been an impediment in the extensive adoption of the cloud computing model. In this regard, advancements in cryptography, accelerated by the wide usage of the internet worldwide, has emerged as a key area in addressing some of these security concerns. In this document, a hybrid cryptographic protocol deploying Blowfish and Paillier encryption algorithms has been presented and its strength compared with… More >

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    ARTICLE

    Collision Observation-Based Optimization of Low-Power and Lossy IoT Network Using Reinforcement Learning

    Arslan Musaddiq1, Rashid Ali2, Jin-Ghoo Choi1, Byung-Seo Kim3,*, Sung-Won Kim1
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 799-814, 2021, DOI:10.32604/cmc.2021.014751
    (This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
    Abstract The Internet of Things (IoT) has numerous applications in every domain, e.g., smart cities to provide intelligent services to sustainable cities. The next-generation of IoT networks is expected to be densely deployed in a resource-constrained and lossy environment. The densely deployed nodes producing radically heterogeneous traffic pattern causes congestion and collision in the network. At the medium access control (MAC) layer, mitigating channel collision is still one of the main challenges of future IoT networks. Similarly, the standardized network layer uses a ranking mechanism based on hop-counts and expected transmission counts (ETX), which often does… More >

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    ARTICLE

    Flower Pollination Heuristics for Nonlinear Active Noise Control Systems

    Wasim Ullah Khan1,*, Yigang He1, Muhammad Asif Zahoor Raja2, Naveed Ishtiaq Chaudhary3, Zeshan Aslam Khan3, Syed Muslim Shah4
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 815-834, 2021, DOI:10.32604/cmc.2021.014674
    Abstract Abstract In this paper, a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems. The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal, random and complex random signals as noise interferences. The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series. The comparative study on statistical observations in terms of… More >

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    ARTICLE

    Geospatial Analytics for COVID-19 Active Case Detection

    Choo-Yee Ting1,*, Helmi Zakariah2, Fadzilah Kamaludin2, Darryl Lin-Wei Cheng1, Nicholas Yu-Zhe Tan1, Hui-Jia Yee2
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 835-848, 2021, DOI:10.32604/cmc.2021.013327
    (This article belongs to the Special Issue: Machine Learning and Computational Methods for COVID-19 Disease Detection and Prediction)
    Abstract Ever since the COVID-19 pandemic started in Wuhan, China, much research work has been focusing on the clinical aspect of SARS-CoV-2. Researchers have been leveraging on various Artificial Intelligence techniques as an alternative to medical approach in understanding the virus. Limited studies have, however, reported on COVID-19 transmission pattern analysis, and using geography features for prediction of potential outbreak sites. Predicting the next most probable outbreak site is crucial, particularly for optimizing the planning of medical personnel and supply resources. To tackle the challenge, this work proposed distance-based similarity measures to predict the next most… More >

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    ARTICLE

    Quality of Service Improvement with Optimal Software-Defined Networking Controller and Control Plane Clustering

    Jehad Ali, Byeong-hee Roh*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 849-875, 2021, DOI:10.32604/cmc.2021.014576
    Abstract The controller is indispensable in software-defined networking (SDN). With several features, controllers monitor the network and respond promptly to dynamic changes. Their performance affects the quality-of-service (QoS) in SDN. Every controller supports a set of features. However, the support of the features may be more prominent in one controller. Moreover, a single controller leads to performance, single-point-of-failure (SPOF), and scalability problems. To overcome this, a controller with an optimum feature set must be available for SDN. Furthermore, a cluster of optimum feature set controllers will overcome an SPOF and improve the QoS in SDN. Herein,… More >

  • Open AccessOpen Access

    ARTICLE

    SwCS: Section-Wise Content Similarity Approach to Exploit Scientific Big Data

    Kashif Irshad1, Muhammad Tanvir Afzal2, Sanam Shahla Rizvi3, Abdul Shahid4, Rabia Riaz5, Tae-Sun Chung6,*
    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 877-894, 2021, DOI:10.32604/cmc.2021.014156
    (This article belongs to the Special Issue: Artificial Intelligence and Big Data in Entrepreneurship)
    Abstract The growing collection of scientific data in various web repositories is referred to as Scientific Big Data, as it fulfills the four “V’s” of Big Data–-volume, variety, velocity, and veracity. This phenomenon has created new opportunities for startups; for instance, the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and entrepreneurs. Traditionally, the content of the papers are compared to list the relevant papers from a repository. The conventional method results in a long list of papers that is often impossible to interpret… More >

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