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  • Open Access

    ARTICLE

    Design and Implementation of Quantum Repeaters: Insights on Quantum Entanglement Purification

    Karoki A. Mũgambi*, Geoffrey O. Okeng’o

    Journal of Quantum Computing, Vol.5, pp. 25-40, 2023, DOI:10.32604/jqc.2023.045654

    Abstract Quantum communication is a groundbreaking technology that is driving the future of information transmission and communication technologies to a new paradigm. It relies on quantum entanglement to facilitate the transmission of quantum states between parties. Quantum repeaters are crucial for facilitating long-distance quantum communication. These quantum devices act as intermediaries between adjacent communication channel segments within a fragmented quantum network, allowing for entanglement swapping between the channel segments. This entanglement swapping process establishes entanglement links between the endpoints of adjacent segments, gradually creating a continuous entanglement connection over the entire length of the transmission channel. The established quantum link can… More >

  • Open Access

    ARTICLE

    Design Optimization of Permanent Magnet Eddy Current Coupler Based on an Intelligence Algorithm

    Dazhi Wang*, Pengyi Pan, Bowen Niu

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1535-1555, 2023, DOI:10.32604/cmc.2023.042286

    Abstract The permanent magnet eddy current coupler (PMEC) solves the problem of flexible connection and speed regulation between the motor and the load and is widely used in electrical transmission systems. It provides torque to the load and generates heat and losses, reducing its energy transfer efficiency. This issue has become an obstacle for PMEC to develop toward a higher power. This paper aims to improve the overall performance of PMEC through multi-objective optimization methods. Firstly, a PMEC modeling method based on the Levenberg-Marquardt back propagation (LMBP) neural network is proposed, aiming at the characteristics of the complex input-output relationship and… More >

  • Open Access

    ARTICLE

    Digital Image Encryption Algorithm Based on Double Chaotic Map and LSTM

    Luoyin Feng1,*, Jize Du2, Chong Fu1

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1645-1662, 2023, DOI:10.32604/cmc.2023.042630

    Abstract In the era of network communication, digital image encryption (DIE) technology is critical to ensure the security of image data. However, there has been limited research on combining deep learning neural networks with chaotic mapping for the encryption of digital images. So, this paper addresses this gap by studying the generation of pseudo-random sequences (PRS) chaotic signals using dual logistic chaotic maps. These signals are then predicted using long and short-term memory (LSTM) networks, resulting in the reconstruction of a new chaotic signal. During the research process, it was discovered that there are numerous training parameters associated with the LSTM… More >

  • Open Access

    ARTICLE

    Effect of Nanomaterials Addition to Phase Change Materials on Heat Transfer in Solar Panels under Iraqi Atmospheric Conditions

    Majid Ahmed Mohammed1, Abdullah Talab Derea2, Mohammed Yaseen Lafta3, Obed Majeed Ali1, Omar Rafae Alomar4,*

    Frontiers in Heat and Mass Transfer, Vol.21, pp. 215-226, 2023, DOI:10.32604/fhmt.2023.041668

    Abstract It is common knowledge that phase-change materials are used for the purpose of thermal storage because of the characteristics that are exclusive to these materials and not found in others. These characteristics include a large capacity for absorbing heat and a large capacity for releasing heat when the phase changes; however, these materials have a low thermal conductivity. This paper presents the results of an experimental study that investigated the impact that nanoparticles of copper oxide had on reducing the temperature of solar panels. The phase change substance that was used was determined to be beeswax. The impact of adding… More >

  • Open Access

    ARTICLE

    A Feasibility Study of Using Geothermal Energy to Enhance Natural Gas Production from Offshore Gas Hydrate Reservoirs by CO2 Swapping

    Md Nahin Mahmood*, Boyun Guo

    Energy Engineering, Vol.120, No.12, pp. 2707-2720, 2023, DOI:10.32604/ee.2023.042996

    Abstract The energy industry faces a significant challenge in extracting natural gas from offshore natural gas hydrate (NGH) reservoirs, primarily due to the low productivity of wells and the high operational costs involved. The present study offers an assessment of the feasibility of utilizing geothermal energy to augment the production of natural gas from offshore gas hydrate reservoirs through the implementation of the methane-CO2 swapping technique. The present study expands the research scope of the authors beyond their previous publication, which exclusively examined the generation of methane from marine gas hydrates. Specifically, the current investigation explores the feasibility of utilizing the… More >

  • Open Access

    ARTICLE

    An Improved Lung Cancer Segmentation Based on Nature-Inspired Optimization Approaches

    Shazia Shamas1, Surya Narayan Panda1,*, Ishu Sharma1,*, Kalpna Guleria1, Aman Singh2,3,4, Ahmad Ali AlZubi5, Mallak Ahmad AlZubi6

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1051-1075, 2024, DOI:10.32604/cmes.2023.030712

    Abstract The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis and planning intervention. This research work addresses the major issues pertaining to the field of medical image processing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposes an improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. The better resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In this process, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarm intelligent techniques. The techniques… More >

  • Open Access

    REVIEW

    A Survey on Sensor- and Communication-Based Issues of Autonomous UAVs

    Pavlo Mykytyn1,2,*, Marcin Brzozowski1, Zoya Dyka1,2, Peter Langendoerfer1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1019-1050, 2024, DOI:10.32604/cmes.2023.029075

    Abstract The application field for Unmanned Aerial Vehicle (UAV) technology and its adoption rate have been increasing steadily in the past years. Decreasing cost of commercial drones has enabled their use at a scale broader than ever before. However, increasing the complexity of UAVs and decreasing the cost, both contribute to a lack of implemented security measures and raise new security and safety concerns. For instance, the issue of implausible or tampered UAV sensor measurements is barely addressed in the current research literature and thus, requires more attention from the research community. The goal of this survey is to extensively review… More >

  • Open Access

    ARTICLE

    Enhanced Tunicate Swarm Optimization with Transfer Learning Enabled Medical Image Analysis System

    Nojood O Aljehane*

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 3109-3126, 2023, DOI:10.32604/csse.2023.038042

    Abstract Medical image analysis is an active research topic, with thousands of studies published in the past few years. Transfer learning (TL) including convolutional neural networks (CNNs) focused to enhance efficiency on an innovative task using the knowledge of the same tasks learnt in advance. It has played a major role in medical image analysis since it solves the data scarcity issue along with that it saves hardware resources and time. This study develops an Enhanced Tunicate Swarm Optimization with Transfer Learning Enabled Medical Image Analysis System (ETSOTL-MIAS). The goal of the ETSOTL-MIAS technique lies in the identification and classification of… More >

  • Open Access

    ARTICLE

    Optimization of CNC Turning Machining Parameters Based on Bp-DWMOPSO Algorithm

    Jiang Li, Jiutao Zhao, Qinhui Liu*, Laizheng Zhu, Jinyi Guo, Weijiu Zhang

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 223-244, 2023, DOI:10.32604/cmc.2023.042429

    Abstract Cutting parameters have a significant impact on the machining effect. In order to reduce the machining time and improve the machining quality, this paper proposes an optimization algorithm based on Bp neural network-Improved Multi-Objective Particle Swarm (Bp-DWMOPSO). Firstly, this paper analyzes the existing problems in the traditional multi-objective particle swarm algorithm. Secondly, the Bp neural network model and the dynamic weight multi-objective particle swarm algorithm model are established. Finally, the Bp-DWMOPSO algorithm is designed based on the established models. In order to verify the effectiveness of the algorithm, this paper obtains the required data through equal probability orthogonal experiments on… More >

  • Open Access

    ARTICLE

    A Spider Monkey Optimization Algorithm Combining Opposition-Based Learning and Orthogonal Experimental Design

    Weizhi Liao1, Xiaoyun Xia1,3, Xiaojun Jia1, Shigen Shen2,*, Helin Zhuang4,*, Xianchao Zhang1

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3297-3323, 2023, DOI:10.32604/cmc.2023.040967

    Abstract As a new bionic algorithm, Spider Monkey Optimization (SMO) has been widely used in various complex optimization problems in recent years. However, the new space exploration power of SMO is limited and the diversity of the population in SMO is not abundant. Thus, this paper focuses on how to reconstruct SMO to improve its performance, and a novel spider monkey optimization algorithm with opposition-based learning and orthogonal experimental design (SMO3) is developed. A position updating method based on the historical optimal domain and particle swarm for Local Leader Phase (LLP) and Global Leader Phase (GLP) is presented to improve the… More >

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