Meshrif Alruily¹, Mohamed Ezz^1,2, Ayman Mohamed Mostafa^1,3, Nacim Yanes^1,4, Mostafa Abbas⁵, Yasser El-Manzalawy^5,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1751-1768, 2022, DOI:10.32604/cmc.2022.020714

Abstract Accurate forecasting of emerging infectious diseases can guide public health officials in making appropriate decisions related to the allocation of public health resources. Due to the exponential spread of the COVID-19 infection worldwide, several computational models for forecasting the transmission and mortality rates of COVID-19 have been proposed in the literature. To accelerate scientific and public health insights into the spread and impact of COVID-19, Google released the Google COVID-19 search trends symptoms open-access dataset. Our objective is to develop 7 and 14-day-ahead forecasting models of COVID-19 transmission and mortality in the US using the Google search trends for COVID-19… More >

Huchen Zhou¹, Wenfeng Huang¹, Mohan Li^1,*, Yulin Lai²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1581-1595, 2022, DOI:10.32604/cmc.2022.020695

Abstract A key aspect of Knowledge fusion is Entity Matching. The objective of this study was to investigate how to identify heterogeneous expressions of the same real-world entity. In recent years, some representative works have used deep learning methods for entity matching, and these methods have achieved good results. However, the common limitation of these methods is that they assume that different attribute columns of the same entity are independent, and inputting the model in the form of paired entity records will cause repeated calculations. In fact, there are often potential relations between different attribute columns of different entities. These relations… More >

Milos Mravik¹, T. Vetriselvi², K. Venkatachalam^3,*, Marko Sarac¹, Nebojsa Bacanin¹, Sasa Adamovic¹

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 457-471, 2022, DOI:10.32604/cmc.2022.020687

Abstract At present, the prevalence of diabetes is increasing because the human body cannot metabolize the glucose level. Accurate prediction of diabetes patients is an important research area. Many researchers have proposed techniques to predict this disease through data mining and machine learning methods. In prediction, feature selection is a key concept in preprocessing. Thus, the features that are relevant to the disease are used for prediction. This condition improves the prediction accuracy. Selecting the right features in the whole feature set is a complicated process, and many researchers are concentrating on it to produce a predictive model with high accuracy.… More >

Siti Hajar Khairuddin, Mohd Hilmi Hasan^*, Emilia Akashah P. Akhir, Manzoor Ahmed Hashmani

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 717-734, 2022, DOI:10.32604/cmc.2022.020666

Abstract Fuzzy inference system (FIS) is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs. The system starts with identifying input from data, applying the fuzziness to input using membership functions (MF), generating fuzzy rules for the fuzzy sets and obtaining the output. There are several types of input MFs which can be introduced in FIS, commonly chosen based on the type of real data, sensitivity of certain rule implied and computational limits. This paper focuses on the construction of interval type 2 (IT2) trapezoidal shape MF from fuzzy C Means (FCM) that is used for… More >

Jinho Bang¹, SongEe Park², Haemin Jeon^2,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1503-1519, 2022, DOI:10.32604/cmc.2022.020485

Abstract Conductive cementitious composites are innovated materials that have improved electrical conductivity compared to general types of cement, and are expected to be used in a variety of future infrastructures with unique functionalities such as self-heating, electromagnetic shielding, and piezoelectricity. In the present study, machine learning methods that have been recently applied in various fields were proposed for the prediction of piezoelectric characteristics of carbon nanotubes (CNTs)-incorporated cement composites. Data on the resistivity change of CNTs/cement composites according to various water/binder ratios, loading types, and CNT content were considered as training values. These data were applied to numerous machine learning techniques… More >

Najib Ahmed Mohammed¹, Ali Mohammed Mansoor^1,*, Rodina Binti Ahmad¹, Saaidal Razalli Bin Azzuhri²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 573-592, 2022, DOI:10.32604/cmc.2022.020462

Abstract Mission critical Machine-type Communication (mcMTC), also referred to as Ultra-reliable Low Latency Communication (URLLC), has become a research hotspot. It is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected devices. While the reduction in physical (PHY) layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability, the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper layers. The mcMTC has a significant technical impact on… More >

Muhammad Samiullah¹, Waqar Aslam¹, Arif Mehmood¹, Muhammad Saeed Ahmad², Shafiq Ahmad³, Adel M. Al-Shayea³, Muhammad Shafiq^4,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 753-769, 2022, DOI:10.32604/cmc.2022.020432

Abstract Smart and interconnected devices can generate meaningful patient data and exchange it automatically without any human intervention in order to realize the Internet of Things (IoT) in healthcare (HIoT). Due to more and more online security and data hijacking attacks, the confidentiality, integrity and availability of data are considered serious issues in HIoT applications. In this regard, lightweight block ciphers (LBCs) are promising in resource-constrained environment where security is the primary consideration. The prevalent challenge while designing an LBC for the HIoT environment is how to ascertain platform performance, cost, and security. Most of the existing LBCs primarily focus on… More >

T. Jeslin^1,*, J. Arul Linsely²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 171-182, 2022, DOI:10.32604/cmc.2022.020255

Abstract Brain cancer is the premier reason for cancer deaths all over the world. The diagnosis of brain cancer at an initial stage is mediocre, as the radiologist is ineffectual. Different experiments have been conducted and demonstrated clearly that the algorithms for nodule segmentation are unsuccessful. Therefore, the research has consolidated incremental clustering focused on superpixel segmentation as an appropriate optimization approach for the accurate segmentation of pulmonary nodules. The key aim of the research is to refine brain CT images to accurately distinguish tumors and the segmentation of small-scale anomalous nodules in the brain region. In the beginning stage, an… More >

Anurag Jain¹, Kusum Yadav², Hadeel Fahad Alharbi², Shamik Tiwari^1,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 423-438, 2022, DOI:10.32604/cmc.2022.020238

Abstract Corona is a viral disease that has taken the form of an epidemic and is causing havoc worldwide after its first appearance in the Wuhan state of China in December 2019. Due to the similarity in initial symptoms with viral fever, it is challenging to identify this virus initially. Non-detection of this virus at the early stage results in the death of the patient. Developing and densely populated countries face a scarcity of resources like hospitals, ventilators, oxygen, and healthcare workers. Technologies like the Internet of Things (IoT) and artificial intelligence can play a vital role in diagnosing the COVID-19… More >

Mohammed Zidan^1,2,*, Manal G. Eldin³, Mahmoud Y. Shams⁴, Mohamed Tolan^5,6, Ayman Abd-Elhamed^2,7, Mahmoud Abdel-Aty⁸

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1065-1078, 2022, DOI:10.32604/cmc.2022.020103

Abstract We present a novel quantum algorithm to evaluate the hamming distance between two unknown oracles via measuring the degree of entanglement between two ancillary qubits. In particular, we use the power of the entanglement degree based quantum computing model that preserves at most the locality of interactions within the quantum model structure. This model uses one of two techniques to retrieve the solution of a quantum computing problem at hand. In the first technique, the solution of the problem is obtained based on whether there is an entanglement between the two ancillary qubits or not. In the second, the solution… More >