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  • Open Access

    ARTICLE

    Hemodynamic Response Detection Using Integrated EEG-fNIRS-VPA for BCI

    Arshia Arif1, M. Jawad Khan1,2,*, Kashif Javed1, Hasan Sajid1,2, Saddaf Rubab1, Noman Naseer3, Talha Irfan Khan4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 535-555, 2022, DOI:10.32604/cmc.2022.018318

    Abstract For BCI systems, it is important to have an accurate and less complex architecture to control a device with enhanced accuracy. In this paper, a novel methodology for more accurate detection of the hemodynamic response has been developed using a multimodal brain-computer interface (BCI). An integrated classifier has been developed for achieving better classification accuracy using two modalities. An integrated EEG-fNIRS-based vector-phase analysis (VPA) has been conducted. An open-source dataset collected at the Technische Universität Berlin, including simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) signals of 26 healthy participants during n-back tests, has been used for this research. Instrumental… More >

  • Open Access

    ARTICLE

    A Hybrid Feature Selection Framework for Predicting Students Performance

    Maryam Zaffar1,2,*, Manzoor Ahmed Hashmani1, Raja Habib2, KS Quraishi3, Muhammad Irfan4, Samar Alqhtani5, Mohammed Hamdi5

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1893-1920, 2022, DOI:10.32604/cmc.2022.018295

    Abstract Student performance prediction helps the educational stakeholders to take proactive decisions and make interventions, for the improvement of quality of education and to meet the dynamic needs of society. The selection of features for student's performance prediction not only plays significant role in increasing prediction accuracy, but also helps in building the strategic plans for the improvement of students’ academic performance. There are different feature selection algorithms for predicting the performance of students, however the studies reported in the literature claim that there are different pros and cons of existing feature selection algorithms in selection of optimal features. In this… More >

  • Open Access

    ARTICLE

    Multiscale Image Dehazing and Restoration: An Application for Visual Surveillance

    Samia Riaz1, Muhammad Waqas Anwar2, Irfan Riaz3, Hyun-Woo Kim4, Yunyoung Nam4,*, Muhammad Attique Khan5

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1-17, 2022, DOI:10.32604/cmc.2022.018268

    Abstract The captured outdoor images and videos may appear blurred due to haze, fog, and bad weather conditions. Water droplets or dust particles in the atmosphere cause the light to scatter, resulting in very limited scene discernibility and deterioration in the quality of the image captured. Currently, image dehazing has gained much popularity because of its usability in a wide variety of applications. Various algorithms have been proposed to solve this ill-posed problem. These algorithms provide quite promising results in some cases, but they include undesirable artifacts and noise in haze patches in adverse cases. Some of these techniques take unrealistic… More >

  • Open Access

    ARTICLE

    Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks

    Mohammad Riyaz Belgaum1, Fuead Ali1, Zainab Alansari2, Shahrulniza Musa1,*, Muhammad Mansoor Alam1,3, M. S. Mazliham4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 251-266, 2022, DOI:10.32604/cmc.2022.018211

    Abstract Software-defined networking (SDN) plays a critical role in transforming networking from traditional to intelligent networking. The increasing demand for services from cloud users has increased the load on the network. An efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service (QoS). The multiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best algorithms. Moreover, the requests need to be transferred to reliable network elements. To address SDN’s current and future… More >

  • Open Access

    ARTICLE

    A Cost-Effective Approach for NDN-Based Internet of Medical Things Deployment

    Syed Sajid Ullah1, Saddam Hussain1, Abdu Gumaei2,3,*, Mohsin S. Alhilal4, Bader Fahad Alkhamees4, Mueen Uddin5, Mabrook Al-Rakhami2

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 233-249, 2022, DOI:10.32604/cmc.2022.017971

    Abstract Nowadays, healthcare has become an important area for the Internet of Things (IoT) to automate healthcare facilities to share and use patient data anytime and anywhere with Internet services. At present, the host-based Internet paradigm is used for sharing and accessing healthcare-related data. However, due to the location-dependent nature, it suffers from latency, mobility, and security. For this purpose, Named Data Networking (NDN) has been recommended as the future Internet paradigm to cover the shortcomings of the traditional host-based Internet paradigm. Unfortunately, the novel breed lacks a secure framework for healthcare. This article constructs an NDN-Based Internet of Medical Things… More >

  • Open Access

    ARTICLE

    Energy Efficient Cluster-Based Optimal Resource Management in IoT Environment

    J. V. Anchitaalagammai1, T. Jayasankar2,*, P. Selvaraj3, Mohamed Yacin Sikkandar4, M. Zakarya5,6, Mohamed Elhoseny7, K. Shankar8

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1247-1261, 2022, DOI:10.32604/cmc.2022.017910

    Abstract Internet of Things (IoT) is a technological revolution that redefined communication and computation of modern era. IoT generally refers to a network of gadgets linked via wireless network and communicates via internet. Resource management, especially energy management, is a critical issue when designing IoT devices. Several studies reported that clustering and routing are energy efficient solutions for optimal management of resources in IoT environment. In this point of view, the current study devises a new Energy-Efficient Clustering-based Routing technique for Resource Management i.e., EECBRM in IoT environment. The proposed EECBRM model has three stages namely, fuzzy logic-based clustering, Lion Whale… More >

  • Open Access

    ARTICLE

    Dynamic Routing Optimization Algorithm for Software Defined Networking

    Nancy Abbas El-Hefnawy1,*, Osama Abdel Raouf2, Heba Askr3

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1349-1362, 2022, DOI:10.32604/cmc.2022.017787

    Abstract Time and space complexity is the most critical problem of the current routing optimization algorithms for Software Defined Networking (SDN). To overcome this complexity, researchers use meta-heuristic techniques inside the routing optimization algorithms in the OpenFlow (OF) based large scale SDNs. This paper proposes a hybrid meta-heuristic algorithm to optimize the dynamic routing problem for the large scale SDNs. Due to the dynamic nature of SDNs, the proposed algorithm uses a mutation operator to overcome the memory-based problem of the ant colony algorithm. Besides, it uses the box-covering method and the k-means clustering method to divide the SDN network to… More >

  • Open Access

    ARTICLE

    Effectively Handling Network Congestion and Load Balancing in Software-Defined Networking

    Shabir Ahmad1, Faisal Jamil2, Abid Ali3, Ehtisham Khan4, Muhammad Ibrahim2, Taeg Keun Whangbo1,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1363-1379, 2022, DOI:10.32604/cmc.2022.017715

    Abstract The concept of Software-Defined Networking (SDN) evolves to overcome the drawbacks of the traditional networks with Internet Protocol (I.P.) packets sending and packets handling. The SDN structure is one of the critical advantages of efficiently separating the data plane from the control plane to manage the network configurations and network management. Whenever there are multiple sending devices inside the SDN network, the OpenFlow switches are programmed to handle the limited number of requests for their interface. When the recommendations are exceeded from the specific threshold, the load on the switches also increases. This research article introduces a new approach named… More >

  • Open Access

    ARTICLE

    Automatic Unusual Activities Recognition Using Deep Learning in Academia

    Muhammad Ramzan1,2,*, Adnan Abid1, Shahid Mahmood Awan1,3

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1829-1844, 2022, DOI:10.32604/cmc.2022.017522

    Abstract In the current era, automatic surveillance has become an active research problem due to its vast real-world applications, particularly for maintaining law and order. A continuous manual monitoring of human activities is a tedious task. The use of cameras and automatic detection of unusual surveillance activity has been growing exponentially over the last few years. Various computer vision techniques have been applied for observation and surveillance of real-world activities. This research study focuses on detecting and recognizing unusual activities in an academic situation such as examination halls, which may help the invigilators observe and restrict the students from cheating or… More >

  • Open Access

    ARTICLE

    A Netnographic-Based Semantic Analysis of Tweet Contents for Stress Management

    Jari Jussila1, Eman Alkhammash2,*, Norah Saleh Alghamdi3, Prashanth Madhala4, Mohammad Ayoub Khan5

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1845-1856, 2022, DOI:10.32604/cmc.2022.017284

    Abstract Social media platforms provide new value for markets and research companies. This article explores the use of social media data to enhance customer value propositions. The case study involves a company that develops wearable Internet of Things (IoT) devices and services for stress management. Netnography and semantic annotation for recognizing and categorizing the context of tweets are conducted to gain a better understanding of users’ stress management practices. The aim is to analyze the tweets about stress management practices and to identify the context from the tweets. Thereafter, we map the tweets on pleasure and arousal to elicit customer insights.… More >

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