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Zia Ul Rehman^1,2, Sagheer Abbas¹, Muhammad Adnan Khan^3,*, Ghulam Mustafa², Hira Fayyaz⁴, Muhammad Hanif^1,2, Muhammad Anwar Saeed⁵
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1075-1090, 2021, DOI:10.32604/cmc.2020.012770
Abstract The internet, particularly online social networking platforms have revolutionized the way extremist groups are influencing and radicalizing individuals. Recent research reveals that the process initiates by exposing vast audiences to extremist content and then migrating potential victims to confined platforms for intensive radicalization. Consequently, social networks have evolved as a persuasive tool for extremism aiding as recruitment platform and psychological warfare. Thus, recognizing potential radical text or material is vital to restrict the circulation of the extremist chronicle. The aim of this research work is to identify radical text in social media. Our contributions are as follows: (i) A new… More >

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Kyungsuk Jang¹, Gun Jin Yun^2,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1091-1120, 2021, DOI:10.32604/cmc.2020.012911
Abstract This paper first proposes a new self-learning data-driven methodology that can develop the failure criteria of unknown anisotropic ductile materials from the minimal number of experimental tests. Establishing failure criteria of anisotropic ductile materials requires time-consuming tests and manual data evaluation. The proposed method can overcome such practical challenges. The methodology is formalized by combining four ideas: 1) The deep learning neural network (DLNN)-based material constitutive model, 2) Self-learning inverse finite element (SELIFE) simulation, 3) Algorithmic identification of failure points from the self-learned stress-strain curves and 4) Derivation of the failure criteria through symbolic regression of the genetic programming. Stress… More >

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Wasfi Shatanawi^1,2,3, Ali Raza^4,5,*, Muhammad Shoaib Arif⁴, Kamaledin Abodayeh¹, Muhammad Rafiq⁶, Mairaj Bibi⁷
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1121-1137, 2021, DOI:10.32604/cmc.2020.012070
（This article belongs to this Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control)
Abstract Nonlinear stochastic modeling plays a significant role in disciplines such as psychology, finance, physical sciences, engineering, econometrics, and biological sciences. Dynamical consistency, positivity, and boundedness are fundamental properties of stochastic modeling. A stochastic coronavirus model is studied with techniques of transition probabilities and parametric perturbation. Well-known explicit methods such as Euler Maruyama, stochastic Euler, and stochastic Runge–Kutta are investigated for the stochastic model. Regrettably, the above essential properties are not restored by existing methods. Hence, there is a need to construct essential properties preserving the computational method. The non-standard approach of finite difference is examined to maintain the above basic… More >

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Rosilah Hassan¹, Selver Pepic², Muzafer Saracevic³, Khaleel Ahmad^4,*, Milan Tasic⁵
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1139-1153, 2021, DOI:10.32604/cmc.2020.013104
（This article belongs to this Special Issue: Deep Learning Trends in Intelligent Systems)
Abstract In this paper, we provide a new approach to data encryption using generalized inverses. Encryption is based on the implementation of weighted Moore–Penrose inverse A^†_MN(nxm) over the nx8 constant matrix. The square Hermitian positive definite matrix N_8x8 p is the key. The proposed solution represents a very strong key since the number of different variants of positive definite matrices of order 8 is huge. We have provided NIST (National Institute of Standards and Technology) quality assurance tests for a random generated Hermitian matrix (a total of 10 different tests and additional analysis with approximate entropy and random digression). In the… More >

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Abdullah Baz^1,*, Hosam Alhakami²
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1155-1174, 2021, DOI:10.32604/cmc.2020.013215
Abstract The World Health Organization declared COVID-19 a pandemic on March 11, 2020 stating that it is a worldwide danger and requires imminent preventive strategies to minimise the loss of lives. COVID-19 has now affected millions across 211 countries in the world and the numbers continue to rise. The information discharged by the WHO till June 15, 2020 reports 8,063,990 cases of COVID-19. As the world thinks about the lethal malady for which there is yet no immunization or a predefined course of drug, the nations are relentlessly working at the most ideal preventive systems to contain the infection. The Kingdom… More >

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Ahmed Bashar Fakhri¹, Saleem Latteef Mohammed¹, Imran Khan², Ali Safaa Sadiq^3,4, Basem Alkazemi⁵, Prashant Pillai⁴, Bong Jun Choi^6,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1175-1194, 2021, DOI:10.32604/cmc.2020.012587
Abstract The development of science and technology has led to the era of Industry 4.0. The core concept is the combination of “material and informationization”. In the supply chain and manufacturing process, the “material” of the physical entity world is realized by data, identity, intelligence, and information. Industry 4.0 is a disruptive transformation and upgrade of intelligent industrialization based on the Internet-of-Things and Big Data in traditional industrialization. The goal is “maximizing production efficiency, minimizing production costs, and maximizing the individual needs of human beings for products and services.” Achieving this goal will surely bring about a major leap in the… More >

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Muhammad Saboor Ahmed^*, Muhammad Tanvir Afzal
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1195-1214, 2021, DOI:10.32604/cmc.2020.012619
Abstract Citations play an important role in the scientific community by assisting in measuring multifarious policies like the impact of journals, researchers, institutions, and countries. Authors cite papers for different reasons, such as extending previous work, comparing their study with the state-of-the-art, providing background of the field, etc. In recent years, researchers have tried to conceptualize all citations into two broad categories, important and incidental. Such a categorization is very important to enhance scientific output in multiple ways, for instance, (1) Helping a researcher in identifying meaningful citations from a list of 100 to 1000 citations (2) Enhancing the impact factor… More >

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1343

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Manjur Kolhar^*, Abdalla Alameen
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1215-1226, 2021, DOI:10.32604/cmc.2020.012658
Abstract Plagiarism refers to the use of other people’s ideas and information without acknowledging the source. In this research, anti-plagiarism software was designed especially for the university and its campuses to identify plagiarized text in students’ written assignments and laboratory reports. The proposed framework collected original documents to identify plagiarized text using natural language processing. Our research proposes a method to detect plagiarism by applying the core concept of text, which is semantic associations of words and their syntactic composition. Information on the browser was obtained through Request application programming interface by name Url.AbsoluteUri, and it is stored in a centralized… More >

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Eman M. A. Hilal¹, E. M. Khalil^2,3,*, S. Abdel-Khalek^2,4
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1227-1236, 2021, DOI:10.32604/cmc.2020.012659
Abstract The effect of the field–field interaction on a cavity containing two qubit (TQ) interacting with a two mode of electromagnetic field as parametric amplifier type is investigated. After performing an appropriate transformation, the constants of motion are calculated. Using the Schrödinger differential equation a system of differential equations was obtained, and the general solution was obtained in the case of exact resonance. Some statistical quantities were calculated and discussed in detail to describe the features of this system. The collapses and revivals phenomena have been discussed in details. The Shannon information entropy has been applied for measuring the degree of… More >

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Raisa Nazir Ahmed Kazi^1,*, Manjur Kolhar², Faiza Rizwan²
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1237-1250, 2021, DOI:10.32604/cmc.2020.012707
Abstract The widespread use of smartwatches has increased their specific and complementary activities in the health sector for patient’s prognosis. In this study, we propose a framework referred to as smart forecasting CardioWatch (SCW) to measure the heart-rate variation (HRV) for patients with myocardial infarction (MI) who live alone or are outside their homes. In this study, HRV is used as a vital alarming sign for patients with MI. The performance of the proposed framework is measured using machine learning and deep learning techniques, namely, support vector machine, logistic regression, and decision-tree classification techniques. The results indicated that the analysis of… More >

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Woong-Kee Loh^*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1251-1267, 2021, DOI:10.32604/cmc.2020.012763
Abstract Many database applications currently deal with objects in a metric space. Examples of such objects include unstructured multimedia objects and points of interest (POIs) in a road network. The M-tree is a dynamic index structure that facilitates an efficient search for objects in a metric space. Studies have been conducted on the bulk loading of large datasets in an M-tree. However, because previous algorithms involve excessive distance computations and disk accesses, they perform poorly in terms of their index construction and search capability. This study proposes two efficient M-tree bulk loading algorithms. Our algorithms minimize the number of distance computations… More >

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Syeda Binish Zahra^1,2, Muhammad Adnan Khan^2,*, Sagheer Abbas¹, Khalid Masood Khan², Mohammed A. Al-Ghamdi³, Sultan H. Almotiri³
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1269-1282, 2021, DOI:10.32604/cmc.2020.012778
Abstract Biomechanics is the study of physiological properties of data and the measurement of human behavior. In normal conditions, behavioural properties in stable form are created using various inputs of subconscious/conscious human activities such as speech style, body movements in walking patterns, writing style and voice tunes. One cannot perform any change in these inputs that make results reliable and increase the accuracy. The aim of our study is to perform a comparative analysis between the marker-based motion capturing system (MBMCS) and the marker-less motion capturing system (MLMCS) using the lower body joint angles of human gait patterns. In both the… More >

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Mosleh M. Abualhaj^1,*, Abdelrahman H. Hussein¹, Manjur Kolhar², Mwaffaq Abu AlHija¹
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1283-1300, 2021, DOI:10.32604/cmc.2020.012991
Abstract The IEEE 802.11n standard has provided prominent features that greatly contribute to ubiquitous wireless networks. Over the last ten years, voice over IP (VoIP) has become widespread around the globe owing to its low-cost or even free call rate. The combination of these technologies (VoIP and wireless) has become desirable and inevitable for organizations. However, VoIP faces a bandwidth utilization issue when working with 802.11 wireless networks. The bandwidth utilization is inefficient on the grounds that (i) 80 bytes of 802.11/RTP/UDP/IP header is appended to 10–730 bytes of VoIP payload and (ii) 765 µs waiting intervals follow each 802.11 VoIP… More >

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Ruaa A. Al-Falluji^1,*, Zainab Dalaf Katheeth², Bashar Alathari²
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1301-1313, 2021, DOI:10.32604/cmc.2020.013232
（This article belongs to this Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
Abstract The latest studies with radiological imaging techniques indicate that X-ray images provide valuable details on the Coronavirus disease 2019 (COVID-19). The usage of sophisticated artificial intelligence technology (AI) and the radiological images can help in diagnosing the disease reliably and addressing the problem of the shortage of trained doctors in remote villages. In this research, the automated diagnosis of Coronavirus disease was performed using a dataset of X-ray images of patients with severe bacterial pneumonia, reported COVID-19 disease, and normal cases. The goal of the study is to analyze the achievements for medical image recognition of state-of-the-art neural networking architectures.… More >

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Salma Kammoun Jarraya^1,2,*, Maha Hamdan Alotibi^1,3, Manar Salamah Ali¹
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1315-1328, 2021, DOI:10.32604/cmc.2020.013522
Abstract With the emergence of the COVID19 virus in late 2019 and the declaration that the virus is a worldwide pandemic, health organizations and governments have begun to implement severe health precautions to reduce the spread of the virus and preserve human lives. The enforcement of social distancing at work environments and public areas is one of these obligatory precautions. Crowd management is one of the effective measures for social distancing. By reducing the social contacts of individuals, the spread of the disease will be immensely reduced. In this paper, a model for crowd counting in public places of high and… More >

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2142

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Sarab AlMuhaideb^*, Reem BinGhannam, Nourah Alhelal, Shatha Alduheshi, Fatimah Alkhamees, Raghad Alsuhaibani
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1329-1346, 2021, DOI:10.32604/cmc.2020.013576
（This article belongs to this Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
Abstract Medical data classification (MDC) refers to the application of classification methods on medical datasets. This work focuses on applying a classification task to medical datasets related to specific diseases in order to predict the associated diagnosis or prognosis. To gain experts’ trust, the prediction and the reasoning behind it are equally important. Accordingly, we confine our research to learn rule-based models because they are transparent and comprehensible. One approach to MDC involves the use of metaheuristic (MH) algorithms. Here we report on the development and testing of a novel MH algorithm: IWD-Miner. This algorithm can be viewed as a fusion… More >

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Naila Habib Khan^1,*, Awais Adnan¹, Abdul Waheed^2,3, Mahdi Zareei⁴, Abdallah Aldosary⁵, Ehab Mahmoud Mohamed^6,7
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1347-1367, 2021, DOI:10.32604/cmc.2020.013715
Abstract Cursive text recognition of Arabic script-based languages like Urdu is extremely complicated due to its diverse and complex characteristics. Evolutionary approaches like genetic algorithms have been used in the past for various optimization as well as pattern recognition tasks, reporting exceptional results. The proposed Urdu ligature recognition system uses a genetic algorithm for optimization and recognition. Overall the proposed recognition system observes the processes of pre-processing, segmentation, feature extraction, hierarchical clustering, classification rules and genetic algorithm optimization and recognition. The pre-processing stage removes noise from the sentence images, whereas, in segmentation, the sentences are segmented into ligature components. Fifteen features… More >

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Yuming Chu^1,2, Muhannad A. Shallal³, Seyed Mehdi Mirhosseini-Alizamini⁴, Hadi Rezazadeh⁵, Shumaila Javeed^6,*, Dumitru Baleanu^7,8
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1369-1378, 2021, DOI:10.32604/cmc.2020.012611
Abstract The purpose of this work is to find new soliton solutions of the complex Ginzburg–Landau equation (GLE) with Kerr law non-linearity. The considered equation is an imperative nonlinear partial differential equation (PDE) in the field of physics. The applications of complex GLE can be found in optics, plasma and other related fields. The modified extended tanh technique with Riccati equation is applied to solve the Complex GLE. The results are presented under a suitable choice for the values of parameters. Figures are shown using the three and two-dimensional plots to represent the shape of the solution in real, and imaginary… More >

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Zhifang Liao¹, Xin Xu¹, Peng Lan¹, Liu Yang¹, Yan Zhang², Xiaoping Fan^3,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1379-1396, 2021, DOI:10.32604/cmc.2020.011995
Abstract In the context of the continuous development of the Internet, crowdsourcing has received continuous attention as a new cooperation model based on the relationship between enterprises, the public and society. Among them, a reasonably designed recommendation algorithm can recommend a batch of suitable workers for crowdsourcing tasks to improve the final task completion quality. Therefore, this paper proposes a crowdsourcing recommendation framework based on workers’ influence (CRBI). This crowdsourcing framework completes the entire process design from task distribution, worker recommendation, and result return through processes such as worker behavior analysis, task characteristics construction, and cost optimization. In this paper, a… More >

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Abdallah Ali Abdallah^*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1397-1410, 2021, DOI:10.32604/cmc.2020.013733
Abstract Lean manufacturing has been used for the last few decades as a process and performance improvement tool. Initially known as Toyota production system (TPS), lean is now used in almost all service and manufacturing sectors to deliver favorable results such as decreased operational cost, increased customer satisfaction, decreased cycle time, and enhanced profits. During the coronavirus disease (COVID 19) pandemic, the manufacturing sector struggled immensely and could not function well even after lockdown was eased in many countries. Many companies found out there are not ready to conform with new regulations made by authorities in many countries. This paper proposes… More >

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Ratha Yeu¹, Namhui Ra², Seong-A Lee³, Yunyoung Nam^4,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1411-1425, 2021, DOI:10.32604/cmc.2020.013761
（This article belongs to this Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
Abstract Electrocardiogram (ECG) electrodes are conductive pads applied to the skin to measure cardiac activity. Ag/AgCl electrodes are the commercial product which widely used to obtain ECGs. When monitoring the ECG in a hot spring, Ag/AgCl electrodes must be waterproofed; however, this is time-consuming, and the adhesive may tear the skin on removal. For solving the problem, we developed the carbon pencil lead (CPL) electrodes for use in hot springs. Both CPL and Ag/AgCl electrodes were connected to ECG100C’s cables. The Performance was evaluated in three conditions as following: hot spring water with and without bubble, and in cold water. In… More >

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Obadah Said Solaiman, Ishak Hashim^*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1427-1444, 2021, DOI:10.32604/cmc.2020.012610
Abstract In this paper, we propose a fifth-order scheme for solving systems of nonlinear equations. The convergence analysis of the proposed technique is discussed. The proposed method is generalized and extended to be of any odd order of the form 2n − 1. The scheme is composed of three steps, of which the first two steps are based on the two-step Homeier’s method with cubic convergence, and the last is a Newton step with an appropriate approximation for the derivative. Every iteration of the presented method requires the evaluation of two functions, two Fréchet derivatives, and three matrix inversions. A comparison… More >

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Anis ur Rehman¹, Farhad Ali¹, Aamina Aamina^2,3,*, Anees Imitaz¹, Ilyas Khan⁴, Kottakkaran Sooppy Nisar⁵
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1445-1459, 2021, DOI:10.32604/cmc.2020.012457
Abstract It is of high interest to study laminar flow with mass and heat transfer phenomena that occur in a viscoelastic fluid taken over a vertical plate due to its importance in many technological processes and its increased industrial applications. Because of its wide range of applications, this study aims at evaluating the solutions corresponding to Casson fluids’ oscillating flow using fractional-derivatives. As it has a combined mass-heat transfer effect, we considered the fluid flow upon an oscillatory infinite vertical-plate. Furthermore, we used two new fractional approaches of fractional derivatives, named AB (Atangana–Baleanu) and CF (Caputo–Fabrizio), on dimensionless governing equations and… More >

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Zaiwar Ali¹, Sadia Khaf², Ziaul Haq Abbas², Ghulam Abbas³, Lei Jiao⁴, Amna Irshad², Kyung Sup Kwak⁵, Muhammad Bilal^6,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1461-1477, 2021, DOI:10.32604/cmc.2020.013743
（This article belongs to this Special Issue: Intelligent techniques for energy efficient service management in Edge computing)
Abstract In mobile edge computing (MEC), one of the important challenges is how much resources of which mobile edge server (MES) should be allocated to which user equipment (UE). The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only. This paper presents a novel comprehensive utility function for resource allocation in MEC. The utility function considers the heterogeneous nature of applications that a UE offloads to MES. The proposed utility function considers all important parameters, including CPU, RAM, hard disk space, required… More >

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Jalal Sadoon Hameed Al-bayati^1,*, Burak Berk Üstündağ²
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1479-1496, 2021, DOI:10.32604/cmc.2020.013329
Abstract The Fused Modified Grasshopper Optimization Algorithm has been proposed, which selects the most specific feature sets from images of the disease of plant leaves. The Proposed algorithm ensures the detection of diseases during the early stages of the diagnosis of leaf disease by farmers and, finally, the crop needed to be controlled by farmers to ensure the survival and protection of plants. In this study, a novel approach has been suggested based on the standard optimization algorithm for grasshopper and the selection of features. Leaf conditions in plants are a major factor in reducing crop yield and quality. Any delay… More >

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Mohammed Kaddi^1,*, Abdallah Banana², Mohammed Omari¹
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1497-1510, 2021, DOI:10.32604/cmc.2020.012116
Abstract Wireless sensor network (WSN) has been widely used due to its vast range of applications. The energy problem is one of the important problems influencing the complete application. Sensor nodes use very small batteries as a power source and replacing them is not an easy task. With this restriction, the sensor nodes must conserve their energy and extend the network lifetime as long as possible. Also, these limits motivate much of the research to suggest solutions in all layers of the protocol stack to save energy. So, energy management efficiency becomes a key requirement in WSN design. The efficiency of… More >

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Changli Lu¹, Ming Zhao^1,2, Imran Khan³, Peerapong Uthansakul^4,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1511-1528, 2021, DOI:10.32604/cmc.2020.012556
Abstract The environmental impact of maritime transport has now become a relevant issue in sustainable policy formulation and has attracted increasing interest from academia. For the sustainable development of maritime transport, International Maritime Organization stipulates that the sulfur content of ship emissions will reach 0.5 from 2020. With the approaching of the stipulated implementation date, shipowners need to adopt scientific methods to make decision on low sulfur fuel. In this study, we applied a prospect theory based hesitant fuzzy multi-criteria decision-making model to obtain the optimal decision of low Sulphur marine fuel. For this purpose, the hesitant fuzzy decision matrix is… More >

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Deepak Prashar¹, Gyanendra Prasad Joshi², Sudan Jha¹, Eunmok Yang³, Kwang Chul Son^4,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1529-1549, 2021, DOI:10.32604/cmc.2020.012986
Abstract The Internet of Things (IoT) is envisioned as a network of various wireless sensor nodes communicating with each other to offer state-of-the-art solutions to real-time problems. These networks of wireless sensors monitor the physical environment and report the collected data to the base station, allowing for smarter decisions. Localization in wireless sensor networks is to localize a sensor node in a two-dimensional plane. However, in some application areas, such as various surveillances, underwater monitoring systems, and various environmental monitoring applications, wireless sensors are deployed in a three-dimensional plane. Recently, localization-based applications have emerged as one of the most promising services… More >

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Jing Hu¹, Ling Zhang¹, Jie Li^2,3,*, Qirun Wang⁴
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1551-1562, 2021, DOI:10.32604/cmc.2020.011829
Abstract Cerebral palsy is a group of persistent central movement and postural developmental disorders, and restricted activity syndromes. This syndrome is caused by non-progressive brain damage to the developing fetus or infants. Cerebral palsy assessment can determine whether the brain is behind or abnormal. If it exists, early intervention and rehabilitation can be carried out as soon as possible to restore brain function to the greatest extent. The direct external manifestation of cerebral palsy is abnormal gait. Accurately determining the muscle strength-related reasons that cause this abnormal gait is the primary problem for treatment. In this paper, clustering methods were used… More >

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Adnan¹, Umar Khan², Naveed Ahmed³, Syed Tauseef Mohyud-Din⁴, Ilyas Khan^5,*, Dumitru Baleanu^6,7,8, Kottakkaran Sooppy Nisar⁹
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1563-1576, 2021, DOI:10.32604/cmc.2020.012326
Abstract Thermal transport investigation in colloidal suspensions is taking a significant research direction. The applications of these fluids are found in various industries, engineering, aerodynamics, mechanical engineering and medical sciences etc. A huge amount of thermal transport is essential in the operation of various industrial production processes. It is a fact that conventional liquids have lower thermal transport characteristics as compared to colloidal suspensions. The colloidal suspensions have high thermal performance due to the thermophysical attributes of the nanoparticles and the host liquid. Therefore, researchers focused on the analysis of the heat transport in nanofluids under diverse circumstances. As such, the… More >

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Srinath Doss¹, Jothi Paranthaman², Suseendran Gopalakrishnan³, Akila Duraisamy³, Souvik Pal⁴, Balaganesh Duraisamy⁵, Chung Le Van^6,*, Dac-Nhuong Le⁷
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1577-1594, 2021, DOI:10.32604/cmc.2020.012379
Abstract In the healthcare system, the Internet of Things (IoT) based distributed systems play a vital role in transferring the medical-related documents and information among the organizations to reduce the replication in medical tests. This datum is sensitive, and hence security is a must in transforming the sensational contents. In this paper, an Evolutionary Algorithm, namely the Memetic Algorithm is used for encrypting the text messages. The encrypted information is then inserted into the medical images using Discrete Wavelet Transform 1 level and 2 levels. The reverse method of the Memetic Algorithm is implemented when extracting a hidden message from the… More >

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Kashif Iqbal^1,2, Sagheer Abbas¹, Muhammad Adnan Khan^3,*, Atifa Athar⁴, Muhammad Saleem Khan¹, Areej Fatima³, Gulzar Ahmad¹
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1595-1612, 2021, DOI:10.32604/cmc.2020.013231
Abstract The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity. Vision-based target detection and object classification have been improved due to the development of deep learning algorithms. Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise, well-engineered, and complete detection of objects, scene or events. The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion detection. In this study… More >

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G. Arun Sampaul Thomas¹, Y. Harold Robinson², E. Golden Julie³, Vimal Shanmuganathan⁴, Seungmin Rho⁵, Yunyoung Nam^6,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1613-1629, 2021, DOI:10.32604/cmc.2020.013443
（This article belongs to this Special Issue: Deep Learning Trends in Intelligent Systems)
Abstract Retinopathy is a human eye disease that causes changes in retinal blood vessels that leads to bleed, leak fluid and vision impairment. Symptoms of retinopathy are blurred vision, changes in color perception, red spots, and eye pain and it cannot be detected with a naked eye. In this paper, a new methodology based on Convolutional Neural Networks (CNN) is developed and proposed to intelligent retinopathy prediction and give a decision about the presence of retinopathy with automatic diabetic retinopathy screening with accurate diagnoses. The CNN model is trained by different images of eyes that have retinopathy and those which do… More >

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Fouzia Nawaz¹, Muhammad Ramzan¹, Khalid Mehmood¹, Hikmat Ullah Khan², Saleem Hayat Khan^3,4, Muhammad Raheel Bhutta^5,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1631-1645, 2021, DOI:10.32604/cmc.2020.012887
（This article belongs to this Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
Abstract Diabetic retinopathy (DR) is a retinal disease that causes irreversible blindness. DR occurs due to the high blood sugar level of the patient, and it is clumsy to be detected at an early stage as no early symptoms appear at the initial level. To prevent blindness, early detection and regular treatment are needed. Automated detection based on machine intelligence may assist the ophthalmologist in examining the patients’ condition more accurately and efficiently. The purpose of this study is to produce an automated screening system for recognition and grading of diabetic retinopathy using machine learning through deep transfer and representational learning.… More >

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Eunmok Yang¹, Gyanendra Prasad Joshi², Changho Seo^3,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1647-1663, 2021, DOI:10.32604/cmc.2020.013210
Abstract In network-based intrusion detection practices, there are more regular instances than intrusion instances. Because there is always a statistical imbalance in the instances, it is difficult to train the intrusion detection system effectively. In this work, we compare intrusion detection performance by increasing the rarely appearing instances rather than by eliminating the frequently appearing duplicate instances. Our technique mitigates the statistical imbalance in these instances. We also carried out an experiment on the training model by increasing the instances, thereby increasing the attack instances step by step up to 13 levels. The experiments included not only known attacks, but also… More >

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K. Shankar^1,*, Eswaran Perumal¹, Mohamed Elhoseny², Phong Thanh Nguyen³
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1665-1680, 2021, DOI:10.32604/cmc.2020.013251
（This article belongs to this Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
Abstract Diabetic retinopathy (DR) is a disease with an increasing prevalence and the major reason for blindness among working-age population. The possibility of severe vision loss can be extensively reduced by timely diagnosis and treatment. An automated screening for DR has been identified as an effective method for early DR detection, which can decrease the workload associated to manual grading as well as save diagnosis costs and time. Several studies have been carried out to develop automated detection and classification models for DR. This paper presents a new IoT and cloud-based deep learning for healthcare diagnosis of Diabetic Retinopathy (DR). The… More >

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AlAli Moneera, AlQahtani Maram, AlJuried Azizah, Taghareed AlOnizan, Dalia Alboqaytah, Nida Aslam^*, Irfan Ullah Khan
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1681-1696, 2021, DOI:10.32604/cmc.2020.013466
Abstract Online advertisements have a significant influence over the success or failure of your business. Therefore, it is important to somehow measure the impact of your advertisement before uploading it online, and this is can be done by calculating the Click Through Rate (CTR). Unfortunately, this method is not eco-friendly, since you have to gather the clicks from users then compute the CTR. This is where CTR prediction come in handy. Advertisement CTR prediction relies on the users’ log regarding click information data. Accurate prediction of CTR is a challenging and critical process for e-advertising platforms these days. CTR prediction uses… More >

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1639

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Yi Liang^1,*, Shaokang Zeng¹, Xiaoxian Xu², Shilu Chang¹, Xing Su¹
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1697-1717, 2021, DOI:10.32604/cmc.2020.012513
Abstract Spark is the most popular in-memory processing framework for big data analytics. Memory is the crucial resource for workloads to achieve performance acceleration on Spark. The extant memory capacity configuration approach in Spark is to statically configure the memory capacity for workloads based on user’s specifications. However, without the deep knowledge of the workload’s system-level characteristics, users in practice often conservatively overestimate the memory utilizations of their workloads and require resource manager to grant more memory share than that they actually need, which leads to the severe waste of memory resources. To address the above issue, SMConf, an automated memory… More >

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1057

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Shahan Yamin Siddiqui^1,2, Sagheer Abbas¹, Muhammad Adnan Khan^3,*, Iftikhar Naseer⁴, Tehreem Masood⁴, Khalid Masood Khan³, Mohammed A. Al Ghamdi⁵, Sultan H. Almotiri⁵
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1719-1732, 2021, DOI:10.32604/cmc.2020.012585
（This article belongs to this Special Issue: Machine Learning and Computational Methods for COVID-19 Disease Detection and Prediction)
Abstract The prompt spread of Coronavirus (COVID-19) subsequently adorns a big threat to the people around the globe. The evolving and the perpetually diagnosis of coronavirus has become a critical challenge for the healthcare sector. Drastically increase of COVID-19 has rendered the necessity to detect the people who are more likely to get infected. Lately, the testing kits for COVID-19 are not available to deal it with required proficiency, along with-it countries have been widely hit by the COVID-19 disruption. To keep in view the need of hour asks for an automatic diagnosis system for early detection of COVID-19. It would… More >

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Haijun Geng^1,2,*, Han Zhang³, Yangyang Zhang⁴
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1733-1744, 2021, DOI:10.32604/cmc.2020.013355
Abstract With an increasing urgent demand for fast recovery routing mechanisms in large-scale networks, minimizing network disruption caused by network failure has become critical. However, a large number of relevant studies have shown that network failures occur on the Internet inevitably and frequently. The current routing protocols deployed on the Internet adopt the reconvergence mechanism to cope with network failures. During the reconvergence process, the packets may be lost because of inconsistent routing information, which reduces the network’s availability greatly and affects the Internet service provider’s (ISP’s) service quality and reputation seriously. Therefore, improving network availability has become an urgent problem.… More >

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Engy El-shafeiy¹, Aboul Ella Hassanien², Karam M. Sallam^3,*, A. A. Abohany⁴
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1745-1755, 2021, DOI:10.32604/cmc.2020.013066
（This article belongs to this Special Issue: Security and Computing in Internet of Things)
Abstract Currently, COVID-19 is spreading all over the world and profoundly impacting people’s lives and economic activities. In this paper, a novel approach called the COVID-19 Quantum Neural Network (CQNN) for predicting the severity of COVID-19 in patients is proposed. It consists of two phases: In the first, the most distinct subset of features in a dataset is identified using a Quick Reduct Feature Selection (QRFS) method to improve its classification performance; and, in the second, machine learning is used to train the quantum neural network to classify the risk. It is found that patients’ serial blood counts (their numbers of… More >

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Khalil Khan¹, Jehad Ali², Kashif Ahmad³, Asma Gul⁴, Ghulam Sarwar⁵, Sahib Khan⁶, Qui Thanh Hoai Ta⁷, Tae-Sun Chung⁸, Muhammad Attique^9,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1757-1770, 2021, DOI:10.32604/cmc.2020.013590
Abstract Face image analysis is one among several important cues in computer vision. Over the last five decades, methods for face analysis have received immense attention due to large scale applications in various face analysis tasks. Face parsing strongly benefits various human face image analysis tasks inducing face pose estimation. In this paper we propose a 3D head pose estimation framework developed through a prior end to end deep face parsing model. We have developed an end to end face parts segmentation framework through deep convolutional neural networks (DCNNs). For training a deep face parts parsing model, we label face images… More >

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Kamlendra Vikram¹, Uvaraja Ragavendran², Kanak Kalita^1,*, Ranjan Kumar Ghadai³, Xiao-Zhi Gao⁴
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1771-1784, 2021, DOI:10.32604/cmc.2020.013946
Abstract In this work, diamond-like carbon (DLC) thin film coatings are deposited on silicon substrates by using plasma-enhanced chemical vapour deposition (PECVD) technique. By varying the hydrogen (H₂) flow rate, CH₄−Argon (Ar) flow rate and deposition temperature (T_d) as per a Box-Behnken experimental design (BBD), 15 DLC deposition experiments are carried out. The Young’s modulus (E) and the coefficient of friction (COF) for the DLCs are measured. By using a second-order polynomial regression approach, two metamodels are built for E and COF, that establish them as functions of H₂ flow rate, CH₄-Ar flow rate and T_d. A non-dominated sorting genetic algorithm… More >

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Amir Haider¹, Muhammad Adnan Khan², Abdur Rehman³, Muhib Ur Rahman⁴, Hyung Seok Kim^1,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1785-1798, 2021, DOI:10.32604/cmc.2020.013910
（This article belongs to this Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract In recent years, cybersecurity has attracted significant interest due to the rapid growth of the Internet of Things (IoT) and the widespread development of computer infrastructure and systems. It is thus becoming particularly necessary to identify cyber-attacks or irregularities in the system and develop an efficient intrusion detection framework that is integral to security. Researchers have worked on developing intrusion detection models that depend on machine learning (ML) methods to address these security problems. An intelligent intrusion detection device powered by data can exploit artificial intelligence (AI), and especially ML, techniques. Accordingly, we propose in this article an intrusion detection… More >

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Hao Zhu^1,*, Mulan Wang², Kun Liu², Weiye Xu³
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1799-1811, 2021, DOI:10.32604/cmc.2020.012706
Abstract In order to solve the problem of complicated Non-Uniform Rational B-Splines (NURBS) modeling and improve the real-time performance of the high-order derivative of the curve interpolation process, the method of NURBS modeling based on the slicing and layering of triangular mesh is introduced. The research and design of NURBS curve interpolation are carried out from the two aspects of software algorithm and hardware structure. Based on the analysis of the characteristics of traditional computing methods with Taylor series expansion, the Adams formula and the Runge-Kutta formula are used in the NURBS curve interpolation process, and the process is then optimized… More >

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Iftikhar Ahmad^1,*, Mohammed A. Alqarni², Abdulwahab Ali Almazroi³, Laiba Alam¹
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1813-1822, 2021, DOI:10.32604/cmc.2020.013048
Abstract Blockchain technology is one of the key technological breakthroughs of the last decade. It has the ability to revolutionize numerous aspects of society, including financial systems, healthcare, e-government and many others. One such area that is able to reap the benefits of blockchain technology is the real estate industry. Like many other industries, real estate faces major administrative problems such as high transaction fees, a lack of transparency, fraud and the effects of a middleman including undue influence and commissions. Blockchain enables supporting technologies to overcome the obstacles inherent within the real estate investment market. These technologies include smart contracts,… More >

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2580

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Olumuyiwa J. Peter¹, Amjad S. Shaikh^2,*, Mohammed O. Ibrahim¹, Kottakkaran Sooppy Nisar³, Dumitru Baleanu^4,5,6, Ilyas Khan⁷, Adesoye I. Abioye¹
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1823-1848, 2021, DOI:10.32604/cmc.2020.012314
（This article belongs to this Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control)
Abstract We propose a mathematical model of the coronavirus disease 2019 (COVID-19) to investigate the transmission and control mechanism of the disease in the community of Nigeria. Using stability theory of differential equations, the qualitative behavior of model is studied. The pandemic indicator represented by basic reproductive number R₀ is obtained from the largest eigenvalue of the next-generation matrix. Local as well as global asymptotic stability conditions for the disease-free and pandemic equilibrium are obtained which determines the conditions to stabilize the exponential spread of the disease. Further, we examined this model by using Atangana–Baleanu fractional derivative operator and existence criteria… More >

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Abdulaziz Attaallah¹, Abdullah Algarni¹, Raees Ahmad Khan^2,*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1849-1865, 2021, DOI:10.32604/cmc.2020.013854
Abstract The advanced technological need, exacerbated by the flexible time constraints, leads to several more design level unexplored vulnerabilities. Security is an extremely vital component in software development; we must take charge of security and therefore analysis of software security risk assumes utmost significance. In order to handle the cyber-security risk of the web application and protect individuals, information and properties effectively, one must consider what needs to be secured, what are the perceived threats and the protection of assets. Security preparation plans, implements, tracks, updates and consistently develops safety risk management activities. Risk management must be interpreted as the major… More >

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1206

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Mikhail Zymbler^*, Alexander Grents, Yana Kraeva, Sachin Kumar
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1867-1878, 2021, DOI:10.32604/cmc.2020.014232
Abstract A discord is a refinement of the concept of an anomalous subsequence of a time series. Being one of the topical issues of time series mining, discords discovery is applied in a wide range of real-world areas (medicine, astronomy, economics, climate modeling, predictive maintenance, energy consumption, etc.). In this article, we propose a novel parallel algorithm for discords discovery on high-performance cluster with nodes based on many-core accelerators in the case when time series cannot fit in the main memory. We assumed that the time series is partitioned across the cluster nodes and achieved parallelization among the cluster nodes as… More >

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2042

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Youseef Alotaibi^*
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1879-1895, 2021, DOI:10.32604/cmc.2020.013739
Abstract A new secured database management system architecture using intrusion detection systems (IDS) is proposed in this paper for organizations with no previous role mapping for users. A simple representation of Structured Query Language queries is proposed to easily permit the use of the worked clustering algorithm. A new clustering algorithm that uses a tube search with adaptive memory is applied to database log files to create users’ profiles. Then, queries issued for each user are checked against the related user profile using a classifier to determine whether or not each query is malicious. The IDS will stop query execution or… More >

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