Wenxia Wang, Jinchen Xu, Xiaodong Ding, Zhihui Song, Yizhen Huang, Xin Zhou, Zheng Shan^*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1363-1390, 2024, DOI:10.32604/cmc.2024.054055 - 15 October 2024

Abstract With the wide application of drone technology, there is an increasing demand for the detection of radar return signals from drones. Existing detection methods mainly rely on time-frequency domain feature extraction and classical machine learning algorithms for image recognition. This method suffers from the problem of large dimensionality of image features, which leads to large input data size and noise affecting learning. Therefore, this paper proposes to extract signal time-domain statistical features for radar return signals from drones and reduce the feature dimension from 512 × 4 to 16 dimensions. However, the downscaled feature data… More >

Iyad Katib¹, Mahmoud Ragab^2,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3749-3765, 2023, DOI:10.32604/csse.2023.036796 - 03 April 2023

Abstract The concept of smart healthcare has seen a gradual increase with the expansion of information technology. Smart healthcare will use a new generation of information technologies, like artificial intelligence, the Internet of Things (IoT), cloud computing, and big data, to transform the conventional medical system in an all-around way, making healthcare highly effective, more personalized, and more convenient. This work designs a new Heap Based Optimization with Deep Quantum Neural Network (HBO-DQNN) model for decision-making in smart healthcare applications. The presented HBO-DQNN model majorly focuses on identifying and classifying healthcare data. In the presented HBO-DQNN… More >

Biswaranjan Panda¹, Nitin Kumar Tripathy¹, Shibashankar Sahu¹, Bikash K. Behera², Walaa E. Elhady^3,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6225-6236, 2022, DOI:10.32604/cmc.2022.028394 - 28 July 2022

Abstract In this paper, we propose a novel algorithm based on Zidan’s quantum computing model for remotely controlling the direction of a quantum-controlled mobile robot equipped with n-movements. The proposed algorithm is based on the measurement of concurrence value for the different movements of the robot. Consider a faraway robot that moves in the deep space (e.g., moves toward a galaxy), and it is required to control the direction of this robot from a ground station by some person Alice. She sends an unknown qubit α |0⟩ + β |1⟩ via the teleportation protocol to the robot. Then,… More >

Engy El-shafeiy¹, Aboul Ella Hassanien², Karam M. Sallam^3,*, A. A. Abohany⁴

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1745-1755, 2021, DOI:10.32604/cmc.2020.013066 - 26 November 2020

Abstract Currently, COVID-19 is spreading all over the world and profoundly impacting people’s lives and economic activities. In this paper, a novel approach called the COVID-19 Quantum Neural Network (CQNN) for predicting the severity of COVID-19 in patients is proposed. It consists of two phases: In the first, the most distinct subset of features in a dataset is identified using a Quick Reduct Feature Selection (QRFS) method to improve its classification performance; and, in the second, machine learning is used to train the quantum neural network to classify the risk. It is found that patients’ serial More >