Zhi Li¹, Yufei Zhao², Yueming Ji², Hanwen Gu², Zaibin Jiao^2,*

Energy Engineering, Vol.121, No.12, pp. 3899-3927, 2024, DOI:10.32604/ee.2024.055899 - 22 November 2024

Abstract By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement, information communication, and other fields, the digital DC distribution network can efficiently and reliably access Distributed Generator (DG) and Energy Storage Systems (ESS), exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play (PnP) operations. However, during device plug-in and -out processes, improper system parameters may lead to small-signal stability issues. Therefore, before executing PnP operations, conducting stability analysis and adjusting parameters swiftly is crucial. This study introduces a four-stage strategy for parameter optimization to enhance… More >

Yucheng Liang^1,2,*, Ke Niu^1,2,*, Yingnan Zhang^1,2, Yifei Meng^1,2, Fangmeng Hu^1,2

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2457-2492, 2024, DOI:10.32604/cmc.2024.056438 - 18 November 2024

Abstract To address the challenges of video copyright protection and ensure the perfect recovery of original video, we propose a dual-domain watermarking scheme for digital video, inspired by Robust Reversible Watermarking (RRW) technology used in digital images. Our approach introduces a parameter optimization strategy that incrementally adjusts scheme parameters through attack simulation fitting, allowing for adaptive tuning of experimental parameters. In this scheme, the low-frequency Polar Harmonic Transform (PHT) moment is utilized as the embedding domain for robust watermarking, enhancing stability against simulation attacks while implementing the parameter optimization strategy. Through extensive attack simulations across various… More >

Yuan Li^1,3,*, Zhiqiang Fan^1,2, Tao Suo^1,3

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.013336

Abstract Light armored vehicles, as the primary means of force transport on contemporary battlefields, require not only high mobility but also better protection to meet the complex battlefield environment and mission requirements. Composite armor is widely used in the design of light armored vehicles due to its lightweight and excellent defensible performance. In this paper, the damage law of the composite armor of an infantry fighting vehicle, when penetrated by fragment-simulated projectiles (FSP), is studied by numerical simulation, and the homogeneous equivalent targets surrogating a combination of local protective armor and vulnerable parts are constructed based More >

Lei Peng^1,*, Jin Zhou², Xianfeng Zhang³, Zhongwei Guan^4,5

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011196

Abstract This paper presents the numerical modelling of the ballistic response of hybrid composite structures subjected to 7.62 mm projectile impact. This study focuses on the modelling of composites made of various materials, including ceramics, Ultra-High-Molecular-Weight Polyethylene (UHMWPE), Kevlar, and compressed wood, with fabrication of hybrid laminated structures that offer promising ballistic resistance capabilities. By employing a range of constitutive models and failure criteria, the finite element model simulates the ballistic behaviors of the constituent materials, facilitating a comprehensive understanding of their performance under high-velocity impacts. The core of the study lies in the comparison between… More >

Yaren Aydın¹, Gebrail Bekdaş^1,*, Sinan Melih Nigdeli¹, Zong Woo Geem^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2471-2499, 2024, DOI:10.32604/cmes.2024.056693 - 31 October 2024

Abstract Dynamic impacts such as wind and earthquakes cause loss of life and economic damage. To ensure safety against these effects, various measures have been taken from past to present and solutions have been developed using different technologies. Tall buildings are more susceptible to vibrations such as wind and earthquakes. Therefore, vibration control has become an important issue in civil engineering. This study optimizes tuned mass damper inerter (TMDI) using far-fault ground motion records. This study derives the optimum parameters of TMDI using the Adaptive Harmony Search algorithm. Structure displacement and total acceleration against earthquake load More >

Nigel Walford^*

Revue Internationale de Géomatique, Vol.33, pp. 445-464, 2024, DOI:10.32604/rig.2024.054535 - 25 October 2024

Abstract The impact of World War II on the physical landscape of British towns and cities as a result of airborne assault is well known. However, less newsworthy but arguably no less significant is the impact of the war on agriculture and the countryside, especially in South-East England. This paper outlines the building of an historical Geographical Information System (GIS) from different data sources including the National Farm Survey (NFS), Luftwaffe and Royal Air Force (RAF) aerial photographs and basic topographic mapping for the South Downs in East and West Sussex. It explores the impact and… More >

Hongsheng Su, Shilin Song^*, Xingsheng Wang

Energy Engineering, Vol.121, No.11, pp. 3289-3303, 2024, DOI:10.32604/ee.2024.054643 - 21 October 2024

Abstract This paper introduces the Particle Swarm Optimization (PSO) algorithm to enhance the Latin Hypercube Sampling (LHS) process. The key objective is to mitigate the issues of lengthy computation times and low computational accuracy typically encountered when applying Monte Carlo Simulation (MCS) to LHS for probabilistic trend calculations. The PSO method optimizes sample distribution, enhances global search capabilities, and significantly boosts computational efficiency. To validate its effectiveness, the proposed method was applied to IEEE34 and IEEE-118 node systems containing wind power. The performance was then compared with Latin Hypercubic Important Sampling (LHIS), which integrates significant sampling More >

Juanling Liang¹, Wenguang Luo^1,2,*, Yongxin Qin¹

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1009-1027, 2024, DOI:10.32604/cmc.2024.055883 - 15 October 2024

Abstract An improved RRT* algorithm, referred to as the AGP-RRT* algorithm, is proposed to address the problems of poor directionality, long generated paths, and slow convergence speed in multi-axis robotic arm path planning. First, an adaptive biased probabilistic sampling strategy is adopted to dynamically adjust the target deviation threshold and optimize the selection of random sampling points and the direction of generating new nodes in order to reduce the search space and improve the search efficiency. Second, a gravitationally adjustable step size strategy is used to guide the search process and dynamically adjust the step-size to… More >

Zeshuang Song¹, Xiao Wang^1,*, Qing Wu¹, Yanting Tao¹, Linghua Xu¹, Yaohua Yin², Jianguo Yan³

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 985-1008, 2024, DOI:10.32604/cmc.2024.055614 - 15 October 2024

Abstract This research is the first application of Unmanned Aerial Vehicles (UAVs) equipped with Multi-access Edge Computing (MEC) servers to offshore wind farms, providing a new task offloading solution to address the challenge of scarce edge servers in offshore wind farms. The proposed strategy is to offload the computational tasks in this scenario to other MEC servers and compute them proportionally, which effectively reduces the computational pressure on local MEC servers when wind turbine data are abnormal. Finally, the task offloading problem is modeled as a multi-intelligent deep reinforcement learning problem, and a task offloading model… More >

Yunfei Ban, Damin Zhang^*, Qing He, Qianwen Shen

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 567-601, 2024, DOI:10.32604/cmc.2024.055007 - 15 October 2024

Abstract The surge in connected devices and massive data aggregation has expanded the scale of the Internet of Things (IoT) networks. The proliferation of unknown attacks and related risks, such as zero-day attacks and Distributed Denial of Service (DDoS) attacks triggered by botnets, have resulted in information leakage and property damage. Therefore, developing an efficient and realistic intrusion detection system (IDS) is critical for ensuring IoT network security. In recent years, traditional machine learning techniques have struggled to learn the complex associations between multidimensional features in network traffic, and the excellent performance of deep learning techniques,… More >