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  • Open Access

    ARTICLE

    Estimator-Based GPS Attitude and Angular Velocity Determination

    Dah-Jing Jwo*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6107-6124, 2022, DOI:10.32604/cmc.2022.024722

    Abstract In this paper, the estimator-based Global Positioning System (GPS) attitude and angular velocity determination is presented. Outputs of the attitude estimator include the attitude angles and attitude rates or body angular velocities, depending on the design of estimator. Traditionally as a position, velocity and time sensor, the GPS also offers a free attitude-determination interferometer. GPS research and applications to the field of attitude determination using carrier phase or Doppler measurement has been extensively conducted. The raw attitude solution using the interferometry technique based on the least-squares approach is inherently noisy. The estimator such as the Kalman filter (KF) or extended… More >

  • Open Access

    ARTICLE

    Optimized Deep Learning Model for Colorectal Cancer Detection and Classification Model

    Mahmoud Ragab1,2,3,*, Khalid Eljaaly4, Maha Farouk S. Sabir5, Ehab Bahaudien Ashary6, S. M. Abo-Dahab7,8, E. M. Khalil3,9

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5751-5764, 2022, DOI:10.32604/cmc.2022.024658

    Abstract The recent developments in biological and information technologies have resulted in the generation of massive quantities of data it speeds up the process of knowledge discovery from biological systems. Due to the advancements of medical imaging in healthcare decision making, significant attention has been paid by the computer vision and deep learning (DL) models. At the same time, the detection and classification of colorectal cancer (CC) become essential to reduce the severity of the disease at an earlier stage. The existing methods are commonly based on the combination of textual features to examine the classifier results or machine learning (ML)… More >

  • Open Access

    ARTICLE

    Exploration of IoT Nodes Communication Using LoRaWAN in Forest Environment

    Anshul Sharma1, Divneet Singh Kapoor1, Anand Nayyar2,3,*, Basit Qureshi4, Kiran Jot Singh1, Khushal Thakur1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6239-6256, 2022, DOI:10.32604/cmc.2022.024639

    Abstract The simultaneous advances in the Internet of Things (IoT), Artificial intelligence (AI) and Robotics is going to revolutionize our world in the near future. In recent years, LoRa (Long Range) wireless powered by LoRaWAN (LoRa Wide Area Network) protocol has attracted the attention of researchers for numerous applications in the IoT domain. LoRa is a low power, unlicensed Industrial, Scientific, and Medical (ISM) band-equipped wireless technology that utilizes a wide area network protocol, i.e., LoRaWAN, to incorporate itself into the network infrastructure. In this paper, we have evaluated the LoRaWAN communication protocol for the implementation of the IoT (Internet of Things)… More >

  • Open Access

    ARTICLE

    LCF: A Deep Learning-Based Lightweight CSI Feedback Scheme for MIMO Networks

    Kyu-haeng Lee*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5561-5580, 2022, DOI:10.32604/cmc.2022.024562

    Abstract Recently, as deep learning technologies have received much attention for their great potential in extracting the principal components of data, there have been many efforts to apply them to the Channel State Information (CSI) feedback overhead problem, which can significantly limit Multi-Input Multi-Output (MIMO) beamforming gains. Unfortunately, since most compression models can quickly become outdated due to channel variation, timely model updates are essential for reflecting the current channel conditions, resulting in frequent additional transmissions for model sharing between transceivers. In particular, the heavy network models employed by most previous studies to achieve high compression gains exacerbate the impact of… More >

  • Open Access

    ARTICLE

    Automated Multi-Document Biomedical Text Summarization Using Deep Learning Model

    Ahmed S. Almasoud1, Siwar Ben Haj Hassine2, Fahd N. Al-Wesabi2,3, Mohamed K. Nour4, Anwer Mustafa Hilal5, Mesfer Al Duhayyim6, Manar Ahmed Hamza5,*, Abdelwahed Motwakel5

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5799-5815, 2022, DOI:10.32604/cmc.2022.024556

    Abstract Due to the advanced developments of the Internet and information technologies, a massive quantity of electronic data in the biomedical sector has been exponentially increased. To handle the huge amount of biomedical data, automated multi-document biomedical text summarization becomes an effective and robust approach of accessing the increased amount of technical and medical literature in the biomedical sector through the summarization of multiple source documents by retaining the significantly informative data. So, multi-document biomedical text summarization acts as a vital role to alleviate the issue of accessing precise and updated information. This paper presents a Deep Learning based Attention Long… More >

  • Open Access

    ARTICLE

    Mathematical Modelling of Quantum Kernel Method for Biomedical Data Analysis

    Mahmoud Ragab1,2,3, Ehab Bahauden Ashary4, Maha Farouk S. Sabir5, Adel A. Bahaddad5, Romany F. Mansour6,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5441-5457, 2022, DOI:10.32604/cmc.2022.024545

    Abstract This study presents a novel method to detect the medical application based on Quantum Computing (QC) and a few Machine Learning (ML) systems. QC has a primary advantage i.e., it uses the impact of quantum parallelism to provide the consequences of prime factorization issue in a matter of seconds. So, this model is suggested for medical application only by recent researchers. A novel strategy i.e., Quantum Kernel Method (QKM) is proposed in this paper for data prediction. In this QKM process, Linear Tunicate Swarm Algorithm (LTSA), the optimization technique is used to calculate the loss function initially and is aimed… More >

  • Open Access

    ARTICLE

    Examination of Pine Wilt Epidemic Model through Efficient Algorithm

    Ali Raza1,*, Emad E. Mahmoud2, A. M. Al-Bugami2, Dumitru Baleanu3,4, Muhammad Rafiq5, Muhammad Mohsin6, Muneerah Al Nuwairan7

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5293-5310, 2022, DOI:10.32604/cmc.2022.024535

    Abstract Pine wilt is a dramatic disease that kills infected trees within a few weeks to a few months. The cause is the pathogen Pinewood Nematode. Most plant-parasitic nematodes are attached to plant roots, but pinewood nematodes are found in the tops of trees. Nematodes kill the tree by feeding the cells around the resin ducts. The modeling of a pine wilt disease is based on six compartments, including three for plants (susceptible trees, exposed trees, and infected trees) and the other for the beetles (susceptible beetles, exposed beetles, and infected beetles). The deterministic modeling, along with subpopulations, is based on… More >

  • Open Access

    ARTICLE

    Annealing Harmony Search Algorithm to Solve the Nurse Rostering Problem

    Mohammed Hadwan1,2,3,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5545-5559, 2022, DOI:10.32604/cmc.2022.024512

    Abstract A real-life problem is the rostering of nurses at hospitals. It is a famous nondeterministic, polynomial time (NP) -hard combinatorial optimization problem. Handling the real-world nurse rostering problem (NRP) constraints in distributing workload equally between available nurses is still a difficult task to achieve. The international shortage of nurses, in addition to the spread of COVID-19, has made it more difficult to provide convenient rosters for nurses. Based on the literature, heuristic-based methods are the most commonly used methods to solve the NRP due to its computational complexity, especially for large rosters. Heuristic-based algorithms in general have problems striking the… More >

  • Open Access

    ARTICLE

    Metaheuristic Based Data Gathering Scheme for Clustered UAVs in 6G Communication Network

    Ahmed S. Almasoud1, Siwar Ben Haj Hassine2, Nadhem NEMRI2, Fahd N. Al-Wesabi2,3, Manar Ahmed Hamza4,*, Anwer Mustafa Hilal4, Abdelwahed Motwakel4, Mesfer Al Duhayyim5

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5311-5325, 2022, DOI:10.32604/cmc.2022.024500

    Abstract The sixth-generation (6G) wireless communication networks are anticipated in integrating aerial, terrestrial, and maritime communication into a robust system to accomplish trustworthy, quick, and low latency needs. It enables to achieve maximum throughput and delay for several applications. Besides, the evolution of 6G leads to the design of unmanned aerial vehicles (UAVs) in providing inexpensive and effective solutions in various application areas such as healthcare, environment monitoring, and so on. In the UAV network, effective data collection with restricted energy capacity poses a major issue to achieving high quality network communication. It can be addressed by the use of clustering… More >

  • Open Access

    ARTICLE

    Echo Location Based Bat Algorithm for Energy Efficient WSN Routing

    Anwer Mustafa Hilal1,*, Siwar Ben Haj Hassine2, Jaber S. Alzahrani3, Masoud Alajmi4, Fahd N. Al-Wesabi2,5, Mesfer Al Duhayyim6, Ishfaq Yaseen1, Abdelwahed Motwakel1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6351-6364, 2022, DOI:10.32604/cmc.2022.024489

    Abstract Due to the wide range of applications, Wireless Sensor Networks (WSN) are increased in day to day life and becomes popular. WSN has marked its importance in both practical and research domains. Energy is the most significant resource, the important challenge in WSN is to extend its lifetime. The energy reduction is a key to extend the network's lifetime. Clustering of sensor nodes is one of the well-known and proved methods for achieving scalable and energy conserving WSN. In this paper, an energy efficient protocol is proposed using metaheuristic Echo location-based BAT algorithm (ECHO-BAT). ECHO-BAT works in two stages. First… More >

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