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  • Open Access


    A Novel Scheduling Framework for Multi-Programming Quantum Computing in Cloud Environment

    Danyang Zheng, Jinchen Xv, Feng Yue, Qiming Du, Zhiheng Wang, Zheng Shan*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1957-1974, 2024, DOI:10.32604/cmc.2024.048956

    Abstract As cloud quantum computing gains broader acceptance, a growing quantity of researchers are directing their focus towards this domain. Nevertheless, the rapid surge in demand for cloud-based quantum computing resources has led to a scarcity, which in turn hampers users from achieving optimal satisfaction. Therefore, cloud quantum computing service providers require a unified analysis and scheduling framework for their quantum resources and user jobs to meet the ever-growing usage demands. This paper introduces a new multi-programming scheduling framework for quantum computing in a cloud environment. The framework addresses the issue of limited quantum computing resources More >

  • Open Access


    Enhancing IoT Security: Quantum-Level Resilience against Threats

    Hosam Alhakami*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 329-356, 2024, DOI:10.32604/cmc.2023.043439

    Abstract The rapid growth of the Internet of Things (IoT) operations has necessitated the incorporation of quantum computing technologies to meet its expanding needs. This integration is motivated by the need to solve the specific issues provided by the expansion of IoT and the potential benefits that quantum computing can offer in this scenario. The combination of IoT and quantum computing creates new privacy and security problems. This study examines the critical need to prevent potential security concerns from quantum computing in IoT applications. We investigate the incorporation of quantum computing approaches within IoT security frameworks,… More >

  • Open Access


    Comparison among Classical, Probabilistic and Quantum Algorithms for Hamiltonian Cycle Problem

    Giuseppe Corrente1,2,*, Carlo Vincenzo Stanzione3,4, Vittoria Stanzione5

    Journal of Quantum Computing, Vol.5, pp. 55-70, 2023, DOI:10.32604/jqc.2023.044786

    Abstract The Hamiltonian cycle problem (HCP), which is an NP-complete problem, consists of having a graph G with nodes and m edges and finding the path that connects each node exactly once. In this paper we compare some algorithms to solve a Hamiltonian cycle problem, using different models of computations and especially the probabilistic and quantum ones. Starting from the classical probabilistic approach of random walks, we take a step to the quantum direction by involving an ad hoc designed Quantum Turing Machine (QTM), which can be a useful conceptual project tool for quantum algorithms. Introducing several More >

  • Open Access


    Pancreatic Cancer Data Classification with Quantum Machine Learning

    Amit Saxena1, Smita Saxena2,*

    Journal of Quantum Computing, Vol.5, pp. 1-13, 2023, DOI:10.32604/jqc.2023.044555

    Abstract Quantum computing is a promising new approach to tackle the complex real-world computational problems by harnessing the power of quantum mechanics principles. The inherent parallelism and exponential computational power of quantum systems hold the potential to outpace classical counterparts in solving complex optimization problems, which are pervasive in machine learning. Quantum Support Vector Machine (QSVM) is a quantum machine learning algorithm inspired by classical Support Vector Machine (SVM) that exploits quantum parallelism to efficiently classify data points in high-dimensional feature spaces. We provide a comprehensive overview of the underlying principles of QSVM, elucidating how different… More >

  • Open Access


    Near Term Hybrid Quantum Computing Solution to the Matrix Riccati Equations

    Augusto González Bonorino1,*, Malick Ndiaye2, Casimer DeCusatis2

    Journal of Quantum Computing, Vol.4, No.3, pp. 135-146, 2022, DOI:10.32604/jqc.2022.036706

    Abstract The well-known Riccati differential equations play a key role in many fields, including problems in protein folding, control and stabilization, stochastic control, and cybersecurity (risk analysis and malware propagation). Quantum computer algorithms have the potential to implement faster approximate solutions to the Riccati equations compared with strictly classical algorithms. While systems with many qubits are still under development, there is significant interest in developing algorithms for near-term quantum computers to determine their accuracy and limitations. In this paper, we propose a hybrid quantum-classical algorithm, the Matrix Riccati Solver (MRS). This approach uses a transformation of More >

  • Open Access


    Quantum Computing Based Neural Networks for Anomaly Classification in Real-Time Surveillance Videos

    MD. Yasar Arafath1,*, A. Niranjil Kumar2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2489-2508, 2023, DOI:10.32604/csse.2023.035732

    Abstract For intelligent surveillance videos, anomaly detection is extremely important. Deep learning algorithms have been popular for evaluating real-time surveillance recordings, like traffic accidents, and criminal or unlawful incidents such as suicide attempts. Nevertheless, Deep learning methods for classification, like convolutional neural networks, necessitate a lot of computing power. Quantum computing is a branch of technology that solves abnormal and complex problems using quantum mechanics. As a result, the focus of this research is on developing a hybrid quantum computing model which is based on deep learning. This research develops a Quantum Computing-based Convolutional Neural Network… More >

  • Open Access


    Quantum Inspired Differential Evolution with Explainable Artificial Intelligence-Based COVID-19 Detection

    Abdullah M. Basahel, Mohammad Yamin*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 209-224, 2023, DOI:10.32604/csse.2023.034449

    Abstract Recent advancements in the Internet of Things (Io), 5G networks, and cloud computing (CC) have led to the development of Human-centric IoT (HIoT) applications that transform human physical monitoring based on machine monitoring. The HIoT systems find use in several applications such as smart cities, healthcare, transportation, etc. Besides, the HIoT system and explainable artificial intelligence (XAI) tools can be deployed in the healthcare sector for effective decision-making. The COVID-19 pandemic has become a global health issue that necessitates automated and effective diagnostic tools to detect the disease at the initial stage. This article presents… More >

  • Open Access


    Quantum Fuzzy Support Vector Machine for Binary Classification

    Xi Huang1,2, Shibin Zhang1,2,*, Chen Lin1,2, Jinyue Xia3

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2783-2794, 2023, DOI:10.32604/csse.2023.032190

    Abstract In the objective world, how to deal with the complexity and uncertainty of big data efficiently and accurately has become the premise and key to machine learning. Fuzzy support vector machine (FSVM) not only deals with the classification problems for training samples with fuzzy information, but also assigns a fuzzy membership degree to each training sample, allowing different training samples to contribute differently in predicting an optimal hyperplane to separate two classes with maximum margin, reducing the effect of outliers and noise, Quantum computing has super parallel computing capabilities and holds the promise of faster… More >

  • Open Access


    An Image Localization System Based on Single Photon

    Yanyi Wu1, Xiaoyu Li2, Qinsheng Zhu1,*, Xiaolei Liu2, Hao Wu1, Shan Yang3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6139-6149, 2022, DOI:10.32604/cmc.2022.032086

    Abstract As an essential part of artificial intelligence, many works focus on image processing which is the branch of computer vision. Nevertheless, image localization faces complex challenges in image processing with image data increases. At the same time, quantum computing has the unique advantages of improving computing power and reducing energy consumption. So, combining the advantage of quantum computing is necessary for studying the quantum image localization algorithms. At present, many quantum image localization algorithms have been proposed, and their efficiency is theoretically higher than the corresponding classical algorithms. But, in quantum computing experiments, quantum gates… More >

  • Open Access


    Controlling Remote Robots Based on Zidan’s Quantum Computing Model

    Biswaranjan Panda1, Nitin Kumar Tripathy1, Shibashankar Sahu1, Bikash K. Behera2, Walaa E. Elhady3,*

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

    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 >

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