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  • Open Access

    ARTICLE

    Clustering Reference Images Based on Covisibility for Visual Localization

    Sangyun Lee1, Junekoo Kang2, Hyunki Hong2,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2705-2725, 2023, DOI:10.32604/cmc.2023.034136 - 31 March 2023

    Abstract In feature-based visual localization for small-scale scenes, local descriptors are used to estimate the camera pose of a query image. For large and ambiguous environments, learning-based hierarchical networks that employ local as well as global descriptors to reduce the search space of database images into a smaller set of reference views have been introduced. However, since global descriptors are generated using visual features, reference images with some of these features may be erroneously selected. In order to address this limitation, this paper proposes two clustering methods based on how often features appear as well as… More >

  • Open Access

    ARTICLE

    WiMA: Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

    Sohaib Manzoor1, Hira Manzoor2, Saddaf Rubab3,4, Muhammad Attique Khan5, Majed Alhaisoni6, Abdullah Alqahtani7, Ye Jin Kim8, Byoungchol Chang9,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2347-2363, 2023, DOI:10.32604/cmc.2023.034044 - 31 March 2023

    Abstract Despite the planned installation and operations of the traditional IEEE 802.11 networks, they still experience degraded performance due to the number of inefficiencies. One of the main reasons is the received signal strength indicator (RSSI) association problem, in which the user remains connected to the access point (AP) unless the RSSI becomes too weak. In this paper, we propose a multi-criterion association (WiMA) scheme based on software defined networking (SDN) in Wi-Fi networks. An association solution based on multi-criterion such as AP load, RSSI, and channel occupancy is proposed to satisfy the quality of service More >

  • Open Access

    ARTICLE

    Deep Transfer Learning-Enabled Activity Identification and Fall Detection for Disabled People

    Majdy M. Eltahir1, Adil Yousif2, Fadwa Alrowais3, Mohamed K. Nour4, Radwa Marzouk5, Hatim Dafaalla6, Asma Abbas Hassan Elnour6, Amira Sayed A. Aziz7, Manar Ahmed Hamza8,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3239-3255, 2023, DOI:10.32604/cmc.2023.034037 - 31 March 2023

    Abstract The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection. This is especially applicable in the case of elderly or disabled people who live self-reliantly in their homes. These sensors produce a huge volume of physical activity data that necessitates real-time recognition, especially during emergencies. Falling is one of the most important problems confronted by older people and people with movement disabilities. Numerous previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled people. But, the costs incurred upon… More >

  • Open Access

    ARTICLE

    Optimizing Resource Allocation Framework for Multi-Cloud Environment

    Tahir Alyas1, Taher M. Ghazal2,3, Badria Sulaiman Alfurhood4, Ghassan F. Issa2, Osama Ali Thawabeh5, Qaiser Abbas6,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4119-4136, 2023, DOI:10.32604/cmc.2023.033916 - 31 March 2023

    Abstract Cloud computing makes dynamic resource provisioning more accessible. Monitoring a functioning service is crucial, and changes are made when particular criteria are surpassed. This research explores the decentralized multi-cloud environment for allocating resources and ensuring the Quality of Service (QoS), estimating the required resources, and modifying allotted resources depending on workload and parallelism due to resources. Resource allocation is a complex challenge due to the versatile service providers and resource providers. The engagement of different service and resource providers needs a cooperation strategy for a sustainable quality of service. The objective of a coherent and… More >

  • Open Access

    ARTICLE

    An IoT Environment Based Framework for Intelligent Intrusion Detection

    Hamza Safwan1, Zeshan Iqbal1, Rashid Amin1, Muhammad Attique Khan2, Majed Alhaisoni3, Abdullah Alqahtani4, Ye Jin Kim5, Byoungchol Chang6,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2365-2381, 2023, DOI:10.32604/cmc.2023.033896 - 31 March 2023

    Abstract Software-defined networking (SDN) represents a paradigm shift in network traffic management. It distinguishes between the data and control planes. APIs are then used to communicate between these planes. The controller is central to the management of an SDN network and is subject to security concerns. This research shows how a deep learning algorithm can detect intrusions in SDN-based IoT networks. Overfitting, low accuracy, and efficient feature selection is all discussed. We propose a hybrid machine learning-based approach based on Random Forest and Long Short-Term Memory (LSTM). In this study, a new dataset based specifically on More >

  • Open Access

    ARTICLE

    SDN-Enabled Content Dissemination Scheme for the Internet of Vehicles

    Abida Sharif1, Muhammad Imran Sharif1, Muhammad Attique Khan2, Nisar Ali2, Abdullah Alqahtani3, Majed Alhaisoni4, Ye Jin Kim5, Byoungchol Chang6,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2383-2396, 2023, DOI:10.32604/cmc.2023.033894 - 31 March 2023

    Abstract The content-centric networking (CCN) architecture allows access to the content through name, instead of the physical location where the content is stored, which makes it a more robust and flexible content-based architecture. Nevertheless, in CCN, the broadcast nature of vehicles on the Internet of Vehicles (IoV) results in latency and network congestion. The IoV-based content distribution is an emerging concept in which all the vehicles are connected via the internet. Due to the high mobility of vehicles, however, IoV applications have different network requirements that differ from those of many other networks, posing new challenges. More >

  • Open Access

    ARTICLE

    Efficient Resource Allocation Algorithm in Uplink OFDM-Based Cognitive Radio Networks

    Omar Abdulghafoor1, Musbah Shaat2, Ibraheem Shayea3, Ahmad Hamood1, Abdelzahir Abdelmaboud4, Ashraf Osman Ibrahim5, Fadhil Mukhlif6,*, Herish Badal1, Norafida Ithnin6, Ali Khadim Lwas7

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3045-3064, 2023, DOI:10.32604/cmc.2023.033888 - 31 March 2023

    Abstract The computational complexity of resource allocation processes, in cognitive radio networks (CRNs), is a major issue to be managed. Furthermore, the complicated solution of the optimal algorithm for handling resource allocation in CRNs makes it unsuitable to adopt in real-world applications where both cognitive users, CRs, and primary users, PUs, exist in the identical geographical area. Hence, this work offers a primarily price-based power algorithm to reduce computational complexity in uplink scenarios while limiting interference to PUs to allowable threshold. Hence, this paper, compared to other frameworks proposed in the literature, proposes a two-step approach… More >

  • Open Access

    ARTICLE

    Network Intrusion Detection Model Using Fused Machine Learning Technique

    Fahad Mazaed Alotaibi*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2479-2490, 2023, DOI:10.32604/cmc.2023.033792 - 31 March 2023

    Abstract With the progress of advanced technology in the industrial revolution encompassing the Internet of Things (IoT) and cloud computing, cyberattacks have been increasing rapidly on a large scale. The rapid expansion of IoT and networks in many forms generates massive volumes of data, which are vulnerable to security risks. As a result, cyberattacks have become a prevalent and danger to society, including its infrastructures, economy, and citizens’ privacy, and pose a national security risk worldwide. Therefore, cyber security has become an increasingly important issue across all levels and sectors. Continuous progress is being made in More >

  • Open Access

    ARTICLE

    Predicting Dementia Risk Factors Based on Feature Selection and Neural Networks

    Ashir Javeed1,2, Ana Luiza Dallora2, Johan Sanmartin Berglund2,*, Arif Ali4, Peter Anderberg2,3, Liaqat Ali5

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2491-2508, 2023, DOI:10.32604/cmc.2023.033783 - 31 March 2023

    Abstract Dementia is a disorder with high societal impact and severe consequences for its patients who suffer from a progressive cognitive decline that leads to increased morbidity, mortality, and disabilities. Since there is a consensus that dementia is a multifactorial disorder, which portrays changes in the brain of the affected individual as early as 15 years before its onset, prediction models that aim at its early detection and risk identification should consider these characteristics. This study aims at presenting a novel method for ten years prediction of dementia using on multifactorial data, which comprised 75 variables.… More >

  • Open Access

    ARTICLE

    Text Simplification Using Transformer and BERT

    Sarah Alissa1,*, Mike Wald2

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3479-3495, 2023, DOI:10.32604/cmc.2023.033647 - 31 March 2023

    Abstract Reading and writing are the main interaction methods with web content. Text simplification tools are helpful for people with cognitive impairments, new language learners, and children as they might find difficulties in understanding the complex web content. Text simplification is the process of changing complex text into more readable and understandable text. The recent approaches to text simplification adopted the machine translation concept to learn simplification rules from a parallel corpus of complex and simple sentences. In this paper, we propose two models based on the transformer which is an encoder-decoder structure that achieves state-of-the-art… More >

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