Rupkumar Mahapatra¹, Sovan Samanta², Madhumangal Pal¹, Jeong-Gon Lee^3,*, Shah Khalid Khan⁴, Usman Naseem⁵, Robin Singh Bhadoria⁶

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1219-1233, 2021, DOI:10.32604/cmc.2021.015590

Abstract Graph colouring is the system of assigning a colour to each vertex of a graph. It is done in such a way that adjacent vertices do not have equal colour. It is fundamental in graph theory. It is often used to solve real-world problems like traffic light signalling, map colouring, scheduling, etc. Nowadays, social networks are prevalent systems in our life. Here, the users are considered as vertices, and their connections/interactions are taken as edges. Some users follow other popular users’ profiles in these networks, and some don’t, but those non-followers are connected directly to the popular profiles. That means,… More >

Muhammad Attique Khan¹, Abdul Majid¹, Tallha Akram², Nazar Hussain¹, Yunyoung Nam^3,*, Seifedine Kadry⁴, Shui-Hua Wang⁵, Majed Alhaisoni⁶

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1003-1019, 2021, DOI:10.32604/cmc.2021.015541

Abstract Here, we use multi-type feature fusion and selection to predict COVID-19 infections on chest computed tomography (CT) scans. The scheme operates in four steps. Initially, we prepared a database containing COVID-19 pneumonia and normal CT scans. These images were retrieved from the Radiopaedia COVID-19 website. The images were divided into training and test sets in a ratio of 70:30. Then, multiple features were extracted from the training data. We used canonical correlation analysis to fuse the features into single vectors; this enhanced the predictive capacity. We next implemented a genetic algorithm (GA) in which an Extreme Learning Machine (ELM) served… More >

Said Ali Hassan¹, Khalid Alnowibet², Prachi Agrawal³, Ali Wagdy Mohamed^4,5,*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1183-1202, 2021, DOI:10.32604/cmc.2021.015514

Abstract Determining the optimum location of facilities is critical in many fields, particularly in healthcare. This study proposes the application of a suitable location model for field hospitals during the novel coronavirus 2019 (COVID-19) pandemic. The used model is the most appropriate among the three most common location models utilized to solve healthcare problems (the set covering model, the maximal covering model, and the P-median model). The proposed nonlinear binary constrained model is a slight modification of the maximal covering model with a set of nonlinear constraints. The model is used to determine the optimum location of field hospitals for COVID-19… More >

R. Thamizhamuthu^*, D. Manjula

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1147-1160, 2021, DOI:10.32604/cmc.2021.015503

Abstract The deadliest type of skin cancer is malignant melanoma. The diagnosis requires at the earliest to reduce the mortality rate. In this study, an efficient Skin Melanoma Classification (SMC) system is presented using dermoscopic images as a non-invasive procedure. The SMC system consists of four modules; segmentation, feature extraction, feature reduction and finally classification. In the first module, k-means clustering is applied to cluster the colour information of dermoscopic images. The second module extracts meaningful and useful descriptors based on the statistics of local property, parameters of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model of wavelet and spatial patterns by Dominant… More >

Said Ali Hassan¹, Khalid Alnowibet^2,3, Prachi Agrawal⁴, Ali Wagdy Mohamed^5,6,*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1161-1181, 2021, DOI:10.32604/cmc.2021.015494

Abstract The optimum delivery of safeguarding substances is a major part of supply chain management and a crucial issue in the mitigation against the outbreak of pandemics. A problem arises for a decision maker who wants to optimally choose a subset of candidate consumers to maximize the distributed quantities of the needed safeguarding substances within a specific time period. A nonlinear binary mathematical programming model for the problem is formulated. The decision variables are binary ones that represent whether to choose a specific consumer, and design constraints are formulated to keep track of the chosen route. To better illustrate the problem,… More >

Bader Rasheed¹, Adil Khan¹, S. M. Ahsan Kazmi², Rasheed Hussain², Md. Jalil Piran^3,*, Doug Young Suh⁴

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 921-939, 2021, DOI:10.32604/cmc.2021.015452

Abstract Detecting malicious Uniform Resource Locators (URLs) is crucially important to prevent attackers from committing cybercrimes. Recent researches have investigated the role of machine learning (ML) models to detect malicious URLs. By using ML algorithms, first, the features of URLs are extracted, and then different ML models are trained. The limitation of this approach is that it requires manual feature engineering and it does not consider the sequential patterns in the URL. Therefore, deep learning (DL) models are used to solve these issues since they are able to perform featureless detection. Furthermore, DL models give better accuracy and generalization to newly… More >

A. F. M. Suaib Akhter^1,*, A. F. M. Shahen Shah², Mohiuddin Ahmed³, Nour Moustafa⁴, Unal Çavuşoğlu¹, Ahmet Zengin¹

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 229-246, 2021, DOI:10.32604/cmc.2021.015447

Abstract Vehicular Ad hoc Networks (VANETs) become a very crucial addition in the Intelligent Transportation System (ITS). It is challenging for a VANET system to provide security services and parallelly maintain high throughput by utilizing limited resources. To overcome these challenges, we propose a blockchain-based Secured Cluster-based MAC (SCB-MAC) protocol. The nearby vehicles heading towards the same direction will form a cluster and each of the clusters has its blockchain to store and distribute the safety messages. The message which contains emergency information and requires Strict Delay Requirement (SDR) for transmission are called safety messages (SM). Cluster Members (CMs) sign SMs… More >

Donghyun Lee, Hosung Park, Soonshin Seo, Changmin Kim, Hyunsoo Son, Gyujin Kim, Ji-Hwan Kim^*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 537-551, 2021, DOI:10.32604/cmc.2021.015430

Abstract A differentiable neural computer (DNC) is analogous to the Von Neumann machine with a neural network controller that interacts with an external memory through an attention mechanism. Such DNC’s offer a generalized method for task-specific deep learning models and have demonstrated reliability with reasoning problems. In this study, we apply a DNC to a language model (LM) task. The LM task is one of the reasoning problems, because it can predict the next word using the previous word sequence. However, memory deallocation is a problem in DNCs as some information unrelated to the input sequence is not allocated and remains… More >

Mahdi H. Miraz^1,2,*, Maaruf Ali³, Peter S. Excell², Sajid Khan⁴

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1021-1039, 2021, DOI:10.32604/cmc.2021.015405

Abstract This paper explains the development of a culturally inclusive ubiquitous M-Learning platform (“Mobile Academy”) with an AI-based adaptive user interface. The rationale and need for this research and development are justified by the continuing widespread adoption of the Internet and Internet enabled devices, especially smartphones. The M-learning platform was designed from the onset for the global traveller. The characteristics and limitations of the application are also discussed. The Mobile Academy, proof of concept prototype, was created to facilitate teaching and learning on the move or in environments where the use of a desktop computer is inconvenient or simply impossible. The… More >

Ajay Arunachalam^1,*, Vinayakumar Ravi², Moez Krichen³, Roobaea Alroobaea⁴, Jehad Saad Alqurni⁵

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 983-1001, 2021, DOI:10.32604/cmc.2021.015371

Abstract One of the key challenges in ad-hoc networks is the resource discovery problem. How efficiently & quickly the queried resource/object can be resolved in such a highly dynamic self-evolving network is the underlying question? Broadcasting is a basic technique in the Mobile Ad-hoc Networks (MANETs), and it refers to sending a packet from one node to every other node within the transmission range. Flooding is a type of broadcast where the received packet is retransmitted once by every node. The naive flooding technique floods the network with query messages, while the random walk scheme operates by contacting subsets of each… More >