Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (24)
  • Open Access

    ARTICLE

    Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

    Li Zheng, Gang Xu*, Wenbin Chen

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 935-957, 2024, DOI:10.32604/cmc.2023.046006

    Abstract Drone logistics is a novel method of distribution that will become prevalent. The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption, resulting in cost savings for the company’s transportation operations. Logistics firms must discern the ideal location for establishing a logistics hub, which is challenging due to the simplicity of existing models and the intricate delivery factors. To simulate the drone logistics environment, this study presents a new mathematical model. The model not only retains the aspects of the current models, but also considers the degree of transportation difficulty from the logistics hub to… More >

  • Open Access

    ARTICLE

    MF2-DMTD: A Formalism and Game-Based Reasoning Framework for Optimized Drone-Type Moving Target Defense

    Sang Seo1, Jaeyeon Lee2, Byeongjin Kim2, Woojin Lee2, Dohoon Kim3,*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2595-2628, 2023, DOI:10.32604/cmc.2023.042668

    Abstract Moving-target-defense (MTD) fundamentally avoids an illegal initial compromise by asymmetrically increasing the uncertainty as the attack surface of the observable defender changes depending on spatial-temporal mutations. However, the existing naive MTD studies were conducted focusing only on wired network mutations. And these cases have also been no formal research on wireless aircraft domains with attributes that are extremely unfavorable to embedded system operations, such as hostility, mobility, and dependency. Therefore, to solve these conceptual limitations, this study proposes normalized drone-type MTD that maximizes defender superiority by mutating the unique fingerprints of wireless drones and that optimizes the period-based mutation principle… 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

    GMLP-IDS: A Novel Deep Learning-Based Intrusion Detection System for Smart Agriculture

    Abdelwahed Berguiga1,2,*, Ahlem Harchay1,2, Ayman Massaoudi1,2, Mossaad Ben Ayed3, Hafedh Belmabrouk4

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 379-402, 2023, DOI:10.32604/cmc.2023.041667

    Abstract Smart Agriculture, also known as Agricultural 5.0, is expected to be an integral part of our human lives to reduce the cost of agricultural inputs, increasing productivity and improving the quality of the final product. Indeed, the safety and ongoing maintenance of Smart Agriculture from cyber-attacks are vitally important. To provide more comprehensive protection against potential cyber-attacks, this paper proposes a new deep learning-based intrusion detection system for securing Smart Agriculture. The proposed Intrusion Detection System IDS, namely GMLP-IDS, combines the feedforward neural network Multilayer Perceptron (MLP) and the Gaussian Mixture Model (GMM) that can better protect the Smart Agriculture… More >

  • Open Access

    ARTICLE

    Efficient Remote Identification for Drone Swarms

    Kang-Moon Seo1, Jane Kim1, Soojin Lee1, Jun-Woo Kwon1, Seung-Hyun Seo1,2,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2937-2958, 2023, DOI:10.32604/cmc.2023.039459

    Abstract With the advancement of unmanned aerial vehicle (UAV) technology, the market for drones and the cooperation of many drones are expanding. Drone swarms move together in multiple regions to perform their tasks. A Ground Control Server (GCS) located in each region identifies drone swarm members to prevent unauthorized drones from trespassing. Studies on drone identification have been actively conducted, but existing studies did not consider multiple drone identification environments. Thus, developing a secure and effective identification mechanism for drone swarms is necessary. We suggested a novel approach for the remote identification of drone swarms. For an efficient identification process between… More >

  • Open Access

    ARTICLE

    Efficient Authentication Scheme for UAV-Assisted Mobile Edge Computing

    Maryam Alhassan, Abdul Raouf Khan*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2727-2740, 2023, DOI:10.32604/cmc.2023.037129

    Abstract Preserving privacy is imperative in the new unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) architecture to ensure that sensitive information is protected and kept secure throughout the communication. Simultaneously, efficiency must be considered while developing such a privacy-preserving scheme because the devices involved in these architectures are resource constrained. This study proposes a lightweight and efficient authentication scheme for the UAV-assisted MEC environment. The proposed scheme is a hardware-based password-less authentication mechanism that is based on the fact that temporal and memory-related efficiency can be significantly improved while maintaining the data security by adopting a hardware-based solution with a… More >

  • Open Access

    ARTICLE

    A Drone-Based Blood Donation Approach Using an Ant Colony Optimization Algorithm

    Sana Abbas1, Faraha Ashraf1, Fahd Jarad2,3,*, Muhammad Shoaib Sardar1, Imran Siddique4

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1917-1930, 2023, DOI:10.32604/cmes.2023.024700

    Abstract This article presents an optimized approach of mathematical techniques in the medical domain by manoeuvring the phenomenon of ant colony optimization algorithm (also known as ACO). A complete graph of blood banks and a path that covers all the blood banks without repeating any link is required by applying the Travelling Salesman Problem (often TSP). The wide use promises to accelerate and offers the opportunity to cultivate health care, particularly in remote or unmerited environments by shrinking lab testing reversal times, empowering just-in-time lifesaving medical supply. More >

  • Open Access

    ARTICLE

    Efficient Deep Learning Framework for Fire Detection in Complex Surveillance Environment

    Naqqash Dilshad1, Taimoor Khan2, JaeSeung Song1,*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 749-764, 2023, DOI:10.32604/csse.2023.034475

    Abstract To prevent economic, social, and ecological damage, fire detection and management at an early stage are significant yet challenging. Although computationally complex networks have been developed, attention has been largely focused on improving accuracy, rather than focusing on real-time fire detection. Hence, in this study, the authors present an efficient fire detection framework termed E-FireNet for real-time detection in a complex surveillance environment. The proposed model architecture is inspired by the VGG16 network, with significant modifications including the entire removal of Block-5 and tweaking of the convolutional layers of Block-4. This results in higher performance with a reduced number of… More >

  • Open Access

    ARTICLE

    Drone for Dynamic Monitoring and Tracking with Intelligent Image Analysis

    Ching-Bang Yao1, Chang-Yi Kao2,*, Jiong-Ting Lin3

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2233-2252, 2023, DOI:10.32604/iasc.2023.034488

    Abstract Traditional monitoring systems that are used in shopping malls or community management, mostly use a remote control to monitor and track specific objects; therefore, it is often impossible to effectively monitor the entire environment. When finding a suspicious person, the tracked object cannot be locked in time for tracking. This research replaces the traditional fixed-point monitor with the intelligent drone and combines the image processing technology and automatic judgment for the movements of the monitored person. This intelligent system can effectively improve the shortcomings of low efficiency and high cost of the traditional monitor system. In this article, we proposed… More >

  • Open Access

    ARTICLE

    Efficient Power Control for UAV Based on Trajectory and Game Theory

    Fadhil Mukhlif1,*, Ashraf Osman Ibrahim2, Norafida Ithnin1, Roobaea Alroobaea3, Majed Alsafyani3

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5589-5606, 2023, DOI:10.32604/cmc.2023.034323

    Abstract Due to the fact that network space is becoming more limited, the implementation of ultra-dense networks (UDNs) has the potential to enhance not only network coverage but also network throughput. Unmanned Aerial Vehicle (UAV) communications have recently garnered a lot of attention due to the fact that they are extremely versatile and may be applied to a wide variety of contexts and purposes. A cognitive UAV is proposed as a solution for the Internet of Things ground terminal’s wireless nodes in this article. In the IoT system, the UAV is utilised not only to determine how the resources should be… More >

Displaying 1-10 on page 1 of 24. Per Page