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  • Open Access

    ARTICLE

    A Secure Multi-factor Authentication Protocol for Healthcare Services Using Cloud-based SDN

    Sugandhi Midha1, Sahil Verma1,*, Kavita1, Mohit Mittal2, Nz Jhanjhi3,4, Mehedi Masud5, Mohammed A. AlZain6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3711-3726, 2023, DOI:10.32604/cmc.2023.027992 - 31 October 2022

    Abstract Cloud-based SDN (Software Defined Network) integration offers new kinds of agility, flexibility, automation, and speed in the network. Enterprises and Cloud providers both leverage the benefits as networks can be configured and optimized based on the application requirement. The integration of cloud and SDN paradigms has played an indispensable role in improving ubiquitous health care services. It has improved the real-time monitoring of patients by medical practitioners. Patients’ data get stored at the central server on the cloud from where it is available to medical practitioners in no time. The centralisation of data on the… More >

  • Open Access

    ARTICLE

    DSAFF-Net: A Backbone Network Based on Mask R-CNN for Small Object Detection

    Jian Peng1,2, Yifang Zhao1,2, Dengyong Zhang1,2,*, Feng Li1,2, Arun Kumar Sangaiah3

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3405-3419, 2023, DOI:10.32604/cmc.2023.027627 - 31 October 2022

    Abstract Recently, object detection based on convolutional neural networks (CNNs) has developed rapidly. The backbone networks for basic feature extraction are an important component of the whole detection task. Therefore, we present a new feature extraction strategy in this paper, which name is DSAFF-Net. In this strategy, we design: 1) a sandwich attention feature fusion module (SAFF module). Its purpose is to enhance the semantic information of shallow features and resolution of deep features, which is beneficial to small object detection after feature fusion. 2) to add a new stage called D-block to alleviate the disadvantages… More >

  • Open Access

    ARTICLE

    Fusion Strategy for Improving Medical Image Segmentation

    Fahad Alraddady1, E. A. Zanaty2, Aida H. Abu bakr3, Walaa M. Abd-Elhafiez4,5,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3627-3646, 2023, DOI:10.32604/cmc.2023.027606 - 31 October 2022

    Abstract In this paper, we combine decision fusion methods with four meta-heuristic algorithms (Particle Swarm Optimization (PSO) algorithm, Cuckoo search algorithm, modification of Cuckoo Search (CS McCulloch) algorithm and Genetic algorithm) in order to improve the image segmentation. The proposed technique based on fusing the data from Particle Swarm Optimization (PSO), Cuckoo search, modification of Cuckoo Search (CS McCulloch) and Genetic algorithms are obtained for improving magnetic resonance images (MRIs) segmentation. Four algorithms are used to compute the accuracy of each method while the outputs are passed to fusion methods. In order to obtain parts of More >

  • Open Access

    ARTICLE

    ETL Maturity Model for Data Warehouse Systems: A CMMI Compliant Framework

    Musawwer Khan1, Islam Ali1, Shahzada Khurram2, Salman Naseer3, Shafiq Ahmad4, Ahmed T. Soliman4, Akber Abid Gardezi5, Muhammad Shafiq6,*, Jin-Ghoo Choi6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3849-3863, 2023, DOI:10.32604/cmc.2023.027387 - 31 October 2022

    Abstract The effectiveness of the Business Intelligence (BI) system mainly depends on the quality of knowledge it produces. The decision-making process is hindered, and the user’s trust is lost, if the knowledge offered is undesired or of poor quality. A Data Warehouse (DW) is a huge collection of data gathered from many sources and an important part of any BI solution to assist management in making better decisions. The Extract, Transform, and Load (ETL) process is the backbone of a DW system, and it is responsible for moving data from source systems into the DW system.… More >

  • Open Access

    ARTICLE

    Few-Shot Object Detection Based on the Transformer and High-Resolution Network

    Dengyong Zhang1,2, Huaijian Pu1,2, Feng Li1,2,*, Xiangling Ding3, Victor S. Sheng4

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3439-3454, 2023, DOI:10.32604/cmc.2023.027267 - 31 October 2022

    Abstract Now object detection based on deep learning tries different strategies. It uses fewer data training networks to achieve the effect of large dataset training. However, the existing methods usually do not achieve the balance between network parameters and training data. It makes the information provided by a small amount of picture data insufficient to optimize model parameters, resulting in unsatisfactory detection results. To improve the accuracy of few shot object detection, this paper proposes a network based on the transformer and high-resolution feature extraction (THR). High-resolution feature extraction maintains the resolution representation of the image. More >

  • Open Access

    ARTICLE

    LoRa Backscatter Network Efficient Data Transmission Using RF Source Range Control

    Dae-Young Kim1, SoYeon Lee2, Seokhoon Kim1,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4015-4025, 2023, DOI:10.32604/cmc.2023.027078 - 31 October 2022

    Abstract Networks based on backscatter communication provide wireless data transmission in the absence of a power source. A backscatter device receives a radio frequency (RF) source and creates a backscattered signal that delivers data; this enables new services in battery-less domains with massive Internet-of-Things (IoT) devices. Connectivity is highly energy-efficient in the context of massive IoT applications. Outdoors, long-range (LoRa) backscattering facilitates large IoT services. A backscatter network guarantees timeslot-and contention-based transmission. Timeslot-based transmission ensures data transmission, but is not scalable to different numbers of transmission devices. If contention-based transmission is used, collisions are unavoidable. To More >

  • Open Access

    ARTICLE

    Identification and Visualization of Spatial and Temporal Trends in Textile Industry

    Umair Yousaf1, Muhammad Asif1, Shahbaz Ahmed1, Noman Tahir1, Azeem Irshad2, Akber Abid Gardezi3, Muhammad Shafiq4,*, Jin-Ghoo Choi4, Habib Hamam5,6,7,8

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4165-4181, 2023, DOI:10.32604/cmc.2023.026607 - 31 October 2022

    Abstract The research volume increases at the study rate, causing massive text corpora. Due to these enormous text corpora, we are drowning in data and starving for information. Therefore, recent research employed different text mining approaches to extract information from this text corpus. These proposed approaches extract meaningful and precise phrases that effectively describe the text's information. These extracted phrases are commonly termed keyphrases. Further, these key phrases are employed to determine the different fields of study trends. Moreover, these key phrases can also be used to determine the spatiotemporal trends in the various research fields.… More >

  • Open Access

    ARTICLE

    Fault Tolerant Optical Mark Recognition

    Qamar Hafeez1, Waqar Aslam1, M. Ikramullah Lali2, Shafiq Ahmad3, Mejdal Alqahtani3, Muhammad Shafiq4,*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3829-3847, 2023, DOI:10.32604/cmc.2023.026422 - 31 October 2022

    Abstract Optical Mark Recognition (OMR) systems have been studied since 1970. It is widely accepted as a data entry technique. OMR technology is used for surveys and multiple-choice questionnaires. Due to its ease of use, OMR technology has grown in popularity over the past two decades and is widely used in universities and colleges to automatically grade and grade student responses to questionnaires. The accuracy of OMR systems is very important due to the environment in which they are used. The OMR algorithm relies on pixel projection or Hough transform to determine the exact answer in… More >

  • Open Access

    ARTICLE

    Automated Deep Learning Based Melanoma Detection and Classification Using Biomedical Dermoscopic Images

    Amani Abdulrahman Albraikan1, Nadhem NEMRI2, Mimouna Abdullah Alkhonaini3, Anwer Mustafa Hilal4,*, Ishfaq Yaseen4, Abdelwahed Motwakel4

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2443-2459, 2023, DOI:10.32604/cmc.2023.026379 - 31 October 2022

    Abstract Melanoma remains a serious illness which is a common form of skin cancer. Since the earlier detection of melanoma reduces the mortality rate, it is essential to design reliable and automated disease diagnosis model using dermoscopic images. The recent advances in deep learning (DL) models find useful to examine the medical image and make proper decisions. In this study, an automated deep learning based melanoma detection and classification (ADL-MDC) model is presented. The goal of the ADL-MDC technique is to examine the dermoscopic images to determine the existence of melanoma. The ADL-MDC technique performs contrast… More >

  • Open Access

    ARTICLE

    A Robust Asynchrophasor in PMU Using Second-Order Kalman Filter

    Nayef Alqahtani1,2,*, Ali Alqahtani3

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2557-2573, 2023, DOI:10.32604/cmc.2023.026316 - 31 October 2022

    Abstract Phasor Measurement Units (PMUs) provide Global Positioning System (GPS) time-stamped synchronized measurements of voltage and current with the phase angle of the system at certain points along with the grid system. Those synchronized data measurements are extracted in the form of amplitude and phase from various locations of the power grid to monitor and control the power system condition. A PMU device is a crucial part of the power equipment in terms of the cost and operative point of view. However, such ongoing development and improvement to PMUs’ principal work are essential to the network… More >

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