Feng Shen^1,*, Yang Zhao¹, Bingyi Li¹, Kai Wu²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 221-243, 2024, DOI:10.32604/cmes.2023.029159

Abstract The calculation of the factor of safety (FOS) is an important means of slope evaluation. This paper proposed an improved double strength reduction method (DRM) to analyze the safety of layered slopes. The physical properties of different soil layers of the slopes are different, so the single coefficient strength reduction method (SRM) is not enough to reflect the actual critical state of the slopes. Considering that the water content of the soil in the natural state is the main factor for the strength of the soil, the attenuation law of shear strength of clayey soil changing with water content is… More >

Zhehan Ji¹, Tongqing Guo^1,*, Di Zhou¹, Zhiliang Lu¹, Binbin Lyu²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 489-508, 2024, DOI:10.32604/cmes.2023.029088

Abstract The reduced weight and improved efficiency of modern aeronautical structures result in a decreasing separation of frequency ranges of rigid and elastic modes. Particularly, a high-aspect-ratio flexible flying wing is prone to body freedom flutter (BFF), which is a result of coupling of the rigid body short-period mode with 1^st wing bending mode. Accurate prediction of the BFF characteristics is helpful to reflect the attitude changes of the vehicle intuitively and design the active flutter suppression control law. Instead of using the rigid body mode, this work simulates the rigid body motion of the model by using the six-degree-of-freedom (6DOF)… More >

Huanhua Liu, Wei Wang^*, Hanyu Liu, Shuheng Yi, Yonghao Yu, Xunwen Yao

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 459-472, 2024, DOI:10.32604/cmes.2023.029084

Abstract Deep Convolutional Neural Networks (CNNs) have achieved high accuracy in image classification tasks, however, most existing models are trained on high-quality images that are not subject to image degradation. In practice, images are often affected by various types of degradation which can significantly impact the performance of CNNs. In this work, we investigate the influence of image degradation on three typical image classification CNNs and propose a Degradation Type Adaptive Image Classification Model (DTA-ICM) to improve the existing CNNs’ classification accuracy on degraded images. The proposed DTA-ICM comprises two key components: a Degradation Type Predictor (DTP) and a Degradation Type… More >

Changfu Wan^1,2, Wenqiang Li^1,2,*, Sitong Ling^1,2, Yingdong Liu^1,2, Jiahao Chen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 321-348, 2024, DOI:10.32604/cmes.2023.029053

Abstract Regarding the spatial profile extraction method of a multi-field co-simulation dataset, different extraction directions, locations, and numbers of profiles will greatly affect the representativeness and integrity of data. In this study, a multi-field co-simulation data extraction method based on adaptive infinitesimal elements is proposed. The multi-field co-simulation dataset based on related infinitesimal elements is constructed, and the candidate directions of data profile extraction undergo dimension reduction by principal component analysis to determine the direction of data extraction. Based on the fireworks algorithm, the data profile with optimal representativeness is searched adaptively in different data extraction intervals to realize the adaptive… More > Graphic Abstract

Xiaofang Kang^1,*, Jian Wu¹, Xinqi Wang¹, Shancheng Lei²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 551-593, 2024, DOI:10.32604/cmes.2023.029044

Abstract In order to improve the seismic performance of adjacent buildings, two types of tuned inerter damper (TID) damping systems for adjacent buildings are proposed, which are composed of springs, inerter devices and dampers in serial or in parallel. The dynamic equations of TID adjacent building damping systems were derived, and the H₂ norm criterion was used to optimize and adjust them, so that the system had the optimum damping performance under white noise random excitation. Taking TID frequency ratio and damping ratio as optimization parameters, the optimum analytical solutions of the displacement frequency response of the undamped structure under white… More > Graphic Abstract

Tao Yin¹, Changgen Peng^2,*, Weijie Tan³, Dequan Xu⁴, Hanlin Tang⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 827-843, 2024, DOI:10.32604/cmes.2023.029039

Abstract In the assessment of car insurance claims, the claim rate for car insurance presents a highly skewed probability distribution, which is typically modeled using Tweedie distribution. The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset, when the data is provided by multiple parties, training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge. To address this issue, this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos. The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection… More >

Senshan Ouyang^1,2, Xiang Liu², Lei Liu², Shangchao Wang², Baichuan Shao³, Yang Zhao^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 903-915, 2024, DOI:10.32604/cmes.2023.028895

Abstract With the continuous expansion of the Industrial Internet of Things (IIoT), more and more organisations are placing large amounts of data in the cloud to reduce overheads. However, the channel between cloud servers and smart equipment is not trustworthy, so the issue of data authenticity needs to be addressed. The SM2 digital signature algorithm can provide an authentication mechanism for data to solve such problems. Unfortunately, it still suffers from the problem of key exposure. In order to address this concern, this study first introduces a key-insulated scheme, SM2-KI-SIGN, based on the SM2 algorithm. This scheme boasts strong key insulation… More >

Huafeng Chen¹, Junxing Xue², Hanyun Wen², Yurong Hu¹, Yudong Zhang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 301-320, 2024, DOI:10.32604/cmes.2023.028738

Abstract Optical image-based ship detection can ensure the safety of ships and promote the orderly management of ships in offshore waters. Current deep learning researches on optical image-based ship detection mainly focus on improving one-stage detectors for real-time ship detection but sacrifices the accuracy of detection. To solve this problem, we present a hybrid ship detection framework which is named EfficientShip in this paper. The core parts of the EfficientShip are DLA-backboned object location (DBOL) and CascadeRCNN-guided object classification (CROC). The DBOL is responsible for finding potential ship objects, and the CROC is used to categorize the potential ship objects. We… More >

Feng Yang¹, Zhong Wu^2,*, Xiaoyan Teng¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 719-738, 2024, DOI:10.32604/cmes.2023.028699

Abstract The low efficiency and high cost of fresh agricultural product terminal distribution directly restrict the operation of the entire supply network. To reduce costs and optimize the distribution network, we construct a mixed integer programming model that comprehensively considers to minimize fixed, transportation, fresh-keeping, time, carbon emissions, and performance incentive costs. We analyzed the performance of traditional rider distribution and robot distribution modes in detail. In addition, the uncertainty of the actual market demand poses a huge threat to the stability of the terminal distribution network. In order to resist uncertain interference, we further extend the model to a robust… More > Graphic Abstract

Md. Shohidul Islam^1,*, Md. Arafatur Rahman², Mohamed Ariff Bin Ameedeen¹, Husnul Ajra¹, Zahian Binti Ismail¹, Jasni Mohamad Zain³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 43-123, 2024, DOI:10.32604/cmes.2023.028687

Abstract Blockchain-enabled cybersecurity system to ensure and strengthen decentralized digital transaction is gradually gaining popularity in the digital era for various areas like finance, transportation, healthcare, education, and supply chain management. Blockchain interactions in the heterogeneous network have fascinated more attention due to the authentication of their digital application exchanges. However, the exponential development of storage space capabilities across the blockchain-based heterogeneous network has become an important issue in preventing blockchain distribution and the extension of blockchain nodes. There is the biggest challenge of data integrity and scalability, including significant computing complexity and inapplicable latency on regional network diversity, operating system… More > Graphic Abstract