Alaa Omran Almagrabi¹, Rashid Ali², Daniyal Alghazzawi¹, Abdullah AlBarakati¹, Tahir Khurshaid^3,*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 359-376, 2021, DOI:10.32604/cmc.2021.014753

Abstract The scope of the Internet of Things (IoT) applications varies from strategic applications, such as smart grids, smart transportation, smart security, and smart healthcare, to industrial applications such as smart manufacturing, smart logistics, smart banking, and smart insurance. In the advancement of the IoT, connected devices become smart and intelligent with the help of sensors and actuators. However, issues and challenges need to be addressed regarding the data reliability and protection for significant next-generation IoT applications like smart healthcare. For these next-generation applications, there is a requirement for far-reaching privacy and security in the IoT. Recently, blockchain systems have emerged… More >

Mazhar Hussain Malik^1,*, Amjed Sid Ahmed¹, Sulaiman Al Hasani²

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 103-115, 2021, DOI:10.32604/cmc.2021.014562

Abstract The COVID-19 pandemic has caused higher educational institutions around the world to close campus-based activities and move to online delivery. The aim of this paper is to present the case of Global College of Engineering and Technology (GCET) and how its practices including teaching, students/staff support, assessments, and exam policies were affected. The paper investigates the mediating role of no detriment policy impact on students’ result along with the challenges faced by the higher educational institution, recommendations and suggestions. The investigation concludes that the strategies adopted for online delivery, student support, assessments and exam policies have helped students to effectively… More >

Oday Ali Hassen¹, Sarmad Omar Abter², Ansam A. Abdulhussein³, Saad M. Darwish^4,*, Yasmine M. Ibrahim⁴, Walaa Sheta⁵

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 961-981, 2021, DOI:10.32604/cmc.2021.014404

Abstract Medical image segmentation has consistently been a significant topic of research and a prominent goal, particularly in computer vision. Brain tumor research plays a major role in medical imaging applications by providing a tremendous amount of anatomical and functional knowledge that enhances and allows easy diagnosis and disease therapy preparation. To prevent or minimize manual segmentation error, automated tumor segmentation, and detection became the most demanding process for radiologists and physicians as the tumor often has complex structures. Many methods for detection and segmentation presently exist, but all lack high accuracy. This paper’s key contribution focuses on evaluating machine learning… More >

Adnan¹, Umar Khan², Naveed Ahmed³, Syed Tauseef Mohyud-Din⁴, Dumitru Baleanu^5,6,7, Kottakkaran Sooppy Nisar⁸, Ilyas Khan^9,*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 213-228, 2021, DOI:10.32604/cmc.2021.014383

Abstract Entropy Generation Optimization (EGO) attained huge interest of scientists and researchers due to its numerous applications comprised in mechanical engineering, air conditioners, heat engines, thermal machines, heat exchange, refrigerators, heat pumps and substance mixing etc. Therefore, the study of radiative hybrid nanofluid (GO-MoS₂/C₂H₆O₂–H₂O) and the conventional nanofluid (MoS₂/C₂H₆O₂–H₂O) is conducted in the presence of Lorentz forces. The flow configuration is modeled between the parallel rotating plates in which the lower plate is permeable. The models which govern the flow in rotating system are solved numerically over the domain of interest and furnished the results for the temperature, entropy generation and… More >

Amjed Sid Ahmed^1,*, Rosilah Hassan², Faizan Qamar³, Mazhar Malik¹

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 247-265, 2021, DOI:10.32604/cmc.2021.014233

Abstract In networking, one major difficulty that nodes suffer from is the need for their addresses to be generated and verified without relying on a third party or public authorized servers. To resolve this issue, the use of self-certifying addresses have become a highly popular and standardized method, of which Cryptographically Generated Addresses (CGA) is a prime example. CGA was primarily designed to deter the theft of IPv6 addresses by binding the generated address to a public key to prove address ownership. Even though the CGA technique is highly effective, this method is still subject to several vulnerabilities with respect to… More >

Nauman Ahmed^1,2, Umbreen Fatima¹, Shahzaib Iqbal¹, Ali Raza³, Muhammad Rafiq^4,*, Muhammad Aziz-ur-Rehman², Shehla Saeed¹, Ilyas Khan⁵, Kottakkaran Sooppy Nisar⁶

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 201-212, 2021, DOI:10.32604/cmc.2021.014171

Abstract The present work is related to the numerical investigation of the spatio-temporal susceptible-latent-breaking out-recovered (SLBR) epidemic model. It describes the computer virus dynamics with vertical transmission via the internet. In these types of dynamics models, the absolute values of the state variables are the fundamental requirement that must be fulfilled by the numerical design. By taking into account this key property, the positivity preserving algorithm is designed to solve the underlying SLBR system. Since, the state variables associated with the phenomenon, represent the computer nodes, so they must take in absolute. Moreover, the continuous system (SLBR) acquires two steady states… More >

Amal S. Hassan¹, Ehab M. Almetwally^2,*, Gamal M. Ibrahim³

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 337-358, 2021, DOI:10.32604/cmc.2021.013971

Abstract In this paper, an attempt is made to discover the distribution of COVID-19 spread in different countries such as; Saudi Arabia, Italy, Argentina and Angola by specifying an optimal statistical distribution for analyzing the mortality rate of COVID-19. A new generalization of the recently inverted Topp Leone distribution, called Kumaraswamy inverted Topp–Leone distribution, is proposed by combining the Kumaraswamy-G family and the inverted Topp–Leone distribution. We initially provide a linear representation of its density function. We give some of its structure properties, such as quantile function, median, moments, incomplete moments, Lorenz and Bonferroni curves, entropies measures and stress-strength reliability. Then,… More >

Belal Al-Khateeb^1,*, Kawther Ahmed², Maha Mahmood¹, Dac-Nhuong Le^3,4

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 643-654, 2021, DOI:10.32604/cmc.2021.013648

Abstract This paper presents a novel metaheuristic algorithm called Rock Hyraxes Swarm Optimization (RHSO) inspired by the behavior of rock hyraxes swarms in nature. The RHSO algorithm mimics the collective behavior of Rock Hyraxes to find their eating and their special way of looking at this food. Rock hyraxes live in colonies or groups where a dominant male watch over the colony carefully to ensure their safety leads the group. Forty-eight (22 unimodal and 26 multimodal) test functions commonly used in the optimization area are used as a testing benchmark for the RHSO algorithm. A comparative efficiency analysis also checks RHSO… More >

Xiaoli Qiang¹, Muhammad Aamir^2,*, Muhammad Naeem², Shaukat Ali³, Adnan Aslam⁴, Zehui Shao¹

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 841-856, 2021, DOI:10.32604/cmc.2021.012540

Abstract COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the world. Forecasting the trend of COVID-19 infections could help in executing policies to effectively reduce the number of new cases. In this study, we apply the decomposition and ensemble model to forecast COVID-19 confirmed cases, deaths, and recoveries in Pakistan for the upcoming month until the end of July. For the decomposition of data, the Ensemble Empirical Mode Decomposition (EEMD) technique is applied. EEMD decomposes the data into small components, called Intrinsic Mode Functions (IMFs). For individual IMFs modelling, we use the Autoregressive Integrated Moving… More >

Shankarnarayanan Nalini^1,*, Nagappan Krishnaraj², Thangaiyan Jayasankar³, Kalimuthu Vinothkumar⁴, Antony Sagai Francis Britto⁵, Kamalraj Subramaniam⁶, Chokkalingam Bharatiraja⁷

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1117-1128, 2021, DOI:10.32604/cmc.2021.012431

Abstract Precision Agriculture is a concept of farm management which makes use of IoT and networking concepts to improve the crop. Plant diseases are one of the underlying causes in the decrease in the number of quantity and quality of the farming crops. Recognition of diseases from the plant images is an active research topic which makes use of machine learning (ML) approaches. A novel deep neural network (DNN) classification model is proposed for the identification of paddy leaf disease using plant image data. Classification errors were minimized by optimizing weights and biases in the DNN model using a crow search… More >