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  • Open Access

    ARTICLE

    Security Requirement Management for Cloud-Assisted and Internet of Things—Enabled Smart City

    Muhammad Usman Tariq1, Muhammad Babar2, Mian Ahmad Jan3,4,5,*, Akmal Saeed Khattak6, Mohammad Dahman Alshehri7, Abid Yahya8

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 625-639, 2021, DOI:10.32604/cmc.2021.014165

    Abstract The world is rapidly changing with the advance of information technology. The expansion of the Internet of Things (IoT) is a huge step in the development of the smart city. The IoT consists of connected devices that transfer information. The IoT architecture permits on-demand services to a public pool of resources. Cloud computing plays a vital role in developing IoT-enabled smart applications. The integration of cloud computing enhances the offering of distributed resources in the smart city. Improper management of security requirements of cloud-assisted IoT systems can bring about risks to availability, security, performance, confidentiality, and privacy. The key reason… More >

  • Open Access

    ARTICLE

    SwCS: Section-Wise Content Similarity Approach to Exploit Scientific Big Data

    Kashif Irshad1, Muhammad Tanvir Afzal2, Sanam Shahla Rizvi3, Abdul Shahid4, Rabia Riaz5, Tae-Sun Chung6,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 877-894, 2021, DOI:10.32604/cmc.2021.014156

    Abstract The growing collection of scientific data in various web repositories is referred to as Scientific Big Data, as it fulfills the four “V’s” of Big Data–-volume, variety, velocity, and veracity. This phenomenon has created new opportunities for startups; for instance, the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and entrepreneurs. Traditionally, the content of the papers are compared to list the relevant papers from a repository. The conventional method results in a long list of papers that is often impossible to interpret productively. Therefore, the need for… More >

  • Open Access

    ARTICLE

    A Weighted Spatially Constrained Finite Mixture Model for Image Segmentation

    Mohammad Masroor Ahmed1,*, Saleh Al Shehri2, Jawad Usman Arshed3, Mahmood Ul Hassan4, Muzammil Hussain5, Mehtab Afzal6

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 171-185, 2021, DOI:10.32604/cmc.2021.014141

    Abstract Spatially Constrained Mixture Model (SCMM) is an image segmentation model that works over the framework of maximum a-posteriori and Markov Random Field (MAP-MRF). It developed its own maximization step to be used within this framework. This research has proposed an improvement in the SCMM’s maximization step for segmenting simulated brain Magnetic Resonance Images (MRIs). The improved model is named as the Weighted Spatially Constrained Finite Mixture Model (WSCFMM). To compare the performance of SCMM and WSCFMM, simulated T1-Weighted normal MRIs were segmented. A region of interest (ROI) was extracted from segmented images. The similarity level between the extracted ROI and… More >

  • Open Access

    ARTICLE

    Toward the Optimization of the Region-Based P300 Speller

    A. Benabid Najjar1,*, N. AlSahly2, R. AlShamass1, M. Hosny2

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1169-1189, 2021, DOI:10.32604/cmc.2021.014140

    Abstract Technology has tremendously contributed to improving communication and facilitating daily activities. Brain-Computer Interface (BCI) study particularly emerged from the need to serve people with disabilities such as Amyotrophic Lateral Sclerosis (ALS). However, with the advancements in cost-effective electronics and computer interface equipment, the BCI study is flourishing, and the exploration of BCI applications for people without disabilities, to enhance normal functioning, is increasing. Particularly, the P300-based spellers are among the most promising applications of the BCI technology. In this context, the region-based paradigm for P300 BCI spellers was introduced in an effort to reduce the crowding effect and adjacency problem… More >

  • Open Access

    ARTICLE

    A Bio-Inspired Routing Optimization in UAV-enabled Internet of Everything

    Masood Ahmad1, Fasee Ullah2,*, Ishtiaq Wahid1, Atif Khan3, M. Irfan Uddin4, Abdullah Alharbi5, Wael Alosaimi5

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 321-336, 2021, DOI:10.32604/cmc.2021.014102

    Abstract Internet of Everything (IoE) indicates a fantastic vision of the future, where everything is connected to the internet, providing intelligent services and facilitating decision making. IoE is the collection of static and moving objects able to coordinate and communicate with each other. The moving objects may consist of ground segments and flying segments. The speed of flying segment e.g., Unmanned Ariel Vehicles (UAVs) may high as compared to ground segment objects. The topology changes occur very frequently due to high speed nature of objects in UAV-enabled IoE (Ue-IoE). The routing maintenance overhead may increase when scaling the Ue-IoE (number of… More >

  • Open Access

    ARTICLE

    Computation Analysis of Brand Experience Dimensions: Indian Online Food Delivery Platforms

    Sufyan Habib1, Nawaf N. Hamadneh2,*, S. Al wadi3, Ra’ed Masa’deh4

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 445-462, 2021, DOI:10.32604/cmc.2021.014047

    Abstract Online Food Delivery Platforms (OFDPs) has witnessed phenomenal growth in the past few years, especially this year due to the COVID-19 pandemic. This Pandemic has forced many governments across the world to give momentum to OFD services and make their presence among the customers. The Presence of several multinational and national companies in this sector has enhanced the competition and companies are trying to adapt various marketing strategies and exploring the brand experience (BEX) dimension that helps in enhancing the brand equity (BE) of OFDPs. BEXs are critical for building brand loyalty (BL) and making companies profitable. Customers can experience… More >

  • Open Access

    ARTICLE

    Authenblue: A New Authentication Protocol for the Industrial Internet of Things

    Rachid Zagrouba1,*, Asayel AlAbdullatif1, Kholood AlAjaji1, Norah Al-Serhani1, Fahd Alhaidari1, Abdullah Almuhaideb2, Atta-ur-Rahman2

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1103-1119, 2021, DOI:10.32604/cmc.2021.014035

    Abstract The Internet of Things (IoT) is where almost anything can be controlled and managed remotely by means of sensors. Although the IoT evolution led to quality of life enhancement, many of its devices are insecure. The lack of robust key management systems, efficient identity authentication, low fault tolerance, and many other issues lead to IoT devices being easily targeted by attackers. In this paper we propose a new authentication protocol called Authenblue that improve the authentication process of IoT devices and Coordinators of Personal Area Network (CPANs) in an Industrial IoT (IIoT) environment. This study proposed Authenblue protocol as a… More >

  • Open Access

    ARTICLE

    Estimating Security Risk of Healthcare Web Applications: A Design Perspective

    Fahad A. Alzahrani*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 187-209, 2021, DOI:10.32604/cmc.2021.014007

    Abstract In the recent years, the booming web-based applications have attracted the hackers’ community. The security risk of the web-based hospital management system (WBHMS) has been increasing rapidly. In the given context, the main goal of all security professionals and website developers is to maintain security divisions and improve on the user’s confidence and satisfaction. At this point, the different WBHMS tackle different types of security risks. In WBHMS, the security of the patients’ medical information is of utmost importance. All in all, there is an inherent security risk of data and assets in the field of the medical industry as… More >

  • Open Access

    ARTICLE

    Intelligent Breast Cancer Prediction Empowered with Fusion and Deep Learning

    Shahan Yamin Siddiqui1,2, Iftikhar Naseer3, Muhammad Adnan Khan4, Muhammad Faheem Mushtaq5, Rizwan Ali Naqvi6,*, Dildar Hussain7, Amir Haider8

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1033-1049, 2021, DOI:10.32604/cmc.2021.013952

    Abstract Breast cancer is the most frequently detected tumor that eventually could result in a significant increase in female mortality globally. According to clinical statistics, one woman out of eight is under the threat of breast cancer. Lifestyle and inheritance patterns may be a reason behind its spread among women. However, some preventive measures, such as tests and periodic clinical checks can mitigate its risk thereby, improving its survival chances substantially. Early diagnosis and initial stage treatment can help increase the survival rate. For that purpose, pathologists can gather support from nondestructive and efficient computer-aided diagnosis (CAD) systems. This study explores… More >

  • Open Access

    ARTICLE

    Smart Object Detection and Home Appliances Control System in Smart Cities

    Sulaiman Khan1, Shah Nazir1, Habib Ullah Khan2,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 895-915, 2021, DOI:10.32604/cmc.2021.013878

    Abstract During the last decade the emergence of Internet of Things (IoT) based applications inspired the world by providing state of the art solutions to many common problems. From traffic management systems to urban cities planning and development, IoT based home monitoring systems, and many other smart applications. Regardless of these facilities, most of these IoT based solutions are data driven and results in small accuracy values for smaller datasets. In order to address this problem, this paper presents deep learning based hybrid approach for the development of an IoT-based intelligent home security and appliance control system in the smart cities.… More >

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