Kumail Javaid¹, Ayesha Siddiqa², Syed Abbas Zilqurnain Naqvi², Allah Ditta³, Muhammad Ahsan², M. A. Khan⁴, Tariq Mahmood⁵, Muhammad Adnan Khan^6,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4425-4442, 2022, DOI:10.32604/cmc.2022.022984

Abstract Artificial intelligence (AI) and machine learning (ML) help in making predictions and businesses to make key decisions that are beneficial for them. In the case of the online shopping business, it’s very important to find trends in the data and get knowledge of features that helps drive the success of the business. In this research, a dataset of 12,330 records of customers has been analyzed who visited an online shopping website over a period of one year. The main objective of this research is to find features that are relevant in terms of correctly predicting the purchasing decisions made by… More >

Palli Padmini¹, C. Paramasivam¹, G. Jyothish Lal², Sadeen Alharbi^3,*, Kaustav Bhowmick⁴

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4523-4554, 2022, DOI:10.32604/cmc.2022.022857

Abstract The present system experimentally demonstrates a synthesis of syllables and words from tongue manoeuvers in multiple languages, captured by four oral sensors only. For an experimental demonstration of the system used in the oral cavity, a prototype tooth model was used. Based on the principle developed in a previous publication by the author(s), the proposed system has been implemented using the oral cavity (tongue, teeth, and lips) features alone, without the glottis and the larynx. The positions of the sensors in the proposed system were optimized based on articulatory (oral cavity) gestures estimated by simulating the mechanism of human speech.… More >

Muhammad Anwar¹, Farhan Masud², Rizwan Aslam Butt³, Sevia Mahdaliza Idrus^4,*, Mohammad Nazir Ahmad⁵, Mohd Yazid Bajuri⁶

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4443-4456, 2022, DOI:10.32604/cmc.2022.022826

Abstract Wireless Body Area Sensor Network (WBASN) is an automated system for remote health monitoring of patients. WBASN under umbrella of Internet of Things (IoT) is comprised of small Biomedical Sensor Nodes (BSNs) that can communicate with each other without human involvement. These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs. The BSNs generate critical data as it is related to patient's health. The data traffic can be classified as Sensitive Data (SD) and Non-sensitive Data (ND) packets based on the value of vital signs. These data packets have… More >

Harmandeep Singh Gill^1,*, Osamah Ibrahim Khalaf², Youseef Alotaibi³, Saleh Alghamdi⁴, Fawaz Alassery⁵

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5135-5150, 2022, DOI:10.32604/cmc.2022.022809

Abstract Fruit classification is found to be one of the rising fields in computer and machine vision. Many deep learning-based procedures worked out so far to classify images may have some ill-posed issues. The performance of the classification scheme depends on the range of captured images, the volume of features, types of characters, choice of features from extracted features, and type of classifiers used. This paper aims to propose a novel deep learning approach consisting of Convolution Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) application to classify the fruit images. Classification accuracy depends on the extracted… More >

Motasem S. Alsawadi^*, Miguel Rio

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4643-4658, 2022, DOI:10.32604/cmc.2022.022783

Abstract Action recognition has been recognized as an activity in which individuals’ behaviour can be observed. Assembling profiles of regular activities such as activities of daily living can support identifying trends in the data during critical events. A skeleton representation of the human body has been proven to be effective for this task. The skeletons are presented in graphs form-like. However, the topology of a graph is not structured like Euclidean-based data. Therefore, a new set of methods to perform the convolution operation upon the skeleton graph is proposed. Our proposal is based on the Spatial Temporal-Graph Convolutional Network (ST-GCN) framework.… More >

Fairuz Shohaimay^1,2, Eddie Shahril Ismail^1,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6125-6145, 2022, DOI:10.32604/cmc.2022.022759

Abstract Communication technology has advanced dramatically amid the 21^st century, increasing the security risk in safeguarding sensitive information. The remote password authentication (RPA) scheme is the simplest cryptosystem that serves as the first line of defence against unauthorised entity attacks. Although the literature contains numerous RPA schemes, to the best of the authors’ knowledge, only few schemes based on the integer factorisation problem (IFP) and the discrete logarithm problem (DLP) that provided a provision for session key agreement to ensure proper mutual authentication. Furthermore, none of the previous schemes provided formal security proof using the random oracle model. Therefore, this study… More >

Chao Ma^1,*, Yinggang Sun¹, Zhenguo Yang¹, Hai Huang¹, Dongyang Zhan^2,3, Jiaxing Qu⁴

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6201-6217, 2022, DOI:10.32604/cmc.2022.022717

Abstract The number of mobile application services is showing an explosive growth trend, which makes it difficult for users to determine which ones are of interest. Especially, the new mobile application services are emerge continuously, most of them have not be rated when they need to be recommended to users. This is the typical problem of cold start in the field of collaborative filtering recommendation. This problem may makes it difficult for users to locate and acquire the services that they actually want, and the accuracy and novelty of service recommendations are also difficult to satisfy users. To solve this problem,… More >

Anwer Mustafa Hilal¹, Fahd N. Al-Wesabi^2,3, Mohamed Tahar Ben Othman⁴, Khaled Mohamad Almustafa⁵, Nadhem Nemri⁶, Mesfer Al Duhayyim⁷, Manar Ahmed Hamza^1,*, Abu Sarwar Zamani¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5979-5994, 2022, DOI:10.32604/cmc.2022.022686

Abstract Presently, cognitive Internet of Things (CIoT) with cloud computing (CC) enabled intelligent healthcare models are developed, which enables communication with intelligent devices, sensor modules, and other stakeholders in the healthcare sector to avail effective decision making. On the other hand, Alzheimer disease (AD) is an advanced and degenerative illness which injures the brain cells, and its earlier detection is necessary for suitable interference by healthcare professional. In this aspect, this paper presents a new Oriented Features from Accelerated Segment Test (FAST) with Rotated Binary Robust Independent Elementary Features (BRIEF) Detector (ORB) with optimal artificial neural network (ORB-OANN) model for AD diagnosis… More >

Chandrashekhar Meshram^1,*, Agbotiname Lucky Imoize^2,3, Sajjad Shaukat Jamal⁴, Amer Aljaedi⁵, Adel R. Alharbi⁵

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4591-4608, 2022, DOI:10.32604/cmc.2022.022642

Abstract The commercialization of the fifth-generation (5G) wireless network has begun. Massive devices are being integrated into 5G-enabled wireless sensor networks (5G WSNs) to deliver a variety of valuable services to network users. However, there are rising fears that 5G WSNs will expose sensitive user data to new security vulnerabilities. For secure end-to-end communication, key agreement and user authentication have been proposed. However, when billions of massive devices are networked to collect and analyze complex user data, more stringent security approaches are required. Data integrity, non-repudiation, and authentication necessitate special-purpose subtree-based signature mechanisms that are pretty difficult to create in practice.… More >

Ivan Izonin^1,*, Roman Tkachenko¹, Michal Gregus², Zoia Duriagina^1,3, Nataliya Shakhovska¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5933-5947, 2022, DOI:10.32604/cmc.2022.022582

Abstract The advent of additive technologies has provided a significant breakthrough in the production of medical implants. It has reduced costs, increased productivity and accuracy of the implant manufacturing process. However, there are problems associated with assessing defects in the microstructure, mechanical and technological properties of alloys, both during their production by powder metallurgy and in the process of 3D printing. Thus traditional research methods of alloys properties demand considerable human, material, and time resources. At the same time, artificial intelligence tools create opportunities for intelligent evaluation of the conformity for the microstructure, phase composition, and properties of titanium powder’s alloys.… More >