Yongfeng Fang^1,3, Kong Fah Tee^2,*

Structural Durability & Health Monitoring, Vol.16, No.2, pp. 129-143, 2022, DOI:10.32604/sdhm.2022.020301

Abstract In this article, structural probabilistic and non-probabilistic reliability have been evaluated and compared under big data condition. Firstly, the big data is collected via structural monitoring and analysis. Big data is classified into different types according to the regularities of the distribution of data. The different stresses which have been subjected by the structure are used in this paper. Secondly, the structural interval reliability and probabilistic prediction models are established by using the stress-strength interference theory under big data of random loads after the stresses and structural strength are comprehensively considered. Structural reliability is computed by using various stress types,… More >

Yu-Fu Ko^1,* , Jiann-Wen Woody Ju²

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.3, pp. 1305-1328, 2021, DOI:10.32604/cmes.2021.017589

Abstract Higher-order multiscale structures are proposed to predict the effective elastic properties of 3-phase particle reinforced composites by considering the probabilistic spherical particles spatial distribution, the particle interactions, and utilizing homogenization with ensemble volume average approach. The matrix material, spherical particles with radius a₁, and spherical particles with radius a₂, are denoted as the 0^th phase, the 1^st phase, and the 2^nd phase, respectively. Particularly, the two inhomogeneity phases are different particle sizes and the same elastic material properties. Improved higher-order (in ratio of spherical particle sizes to the distance between the centers of spherical particles) bounds on effective elastic properties… More >

R. Sakunthala Jenni^*, S. Shankar

Computer Systems Science and Engineering, Vol.41, No.2, pp. 525-538, 2022, DOI:10.32604/csse.2022.019300

Abstract The detection of phishing and legitimate websites is considered a great challenge for web service providers because the users of such websites are indistinguishable. Phishing websites also create traffic in the entire network. Another phishing issue is the broadening malware of the entire network, thus highlighting the demand for their detection while massive datasets (i.e., big data) are processed. Despite the application of boosting mechanisms in phishing detection, these methods are prone to significant errors in their output, specifically due to the combination of all website features in the training state. The upcoming big data system requires MapReduce, a popular… More >

Zhen Xu¹, Xiaoqian Zeng¹, Genlin Ji^1,*, Bo Sheng²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1703-1717, 2022, DOI:10.32604/iasc.2022.016919

Abstract Anomaly detection in surveillance videos is an extremely challenging task due to the ambiguous definitions for abnormality. In a complex surveillance scenario, the kinds of abnormal events are numerous and might co-exist, including such as appearance and motion anomaly of objects, long-term abnormal activities, etc. Traditional video anomaly detection methods cannot detect all these kinds of abnormal events. Hence, we utilize multiple probabilistic models inference to detect as many different kinds of abnormal events as possible. To depict realistic events in a scene, the parameters of our methods are tailored to the characteristics of video sequences of practical surveillance scenarios.… More >

Bo Mi¹, Yuan Weng¹, Darong Huang^1,*, Yang Liu¹, Yuqing Gan²

Computer Systems Science and Engineering, Vol.39, No.2, pp. 265-274, 2021, DOI:10.32604/csse.2021.017507

Abstract PoW (Proof of Work) plays a significant role in most blockchain systems to grant an accounting right over decentralized participants and ensure tamper resistance. Though hash functions are generally exploited for PoW due to their merits on summering, anti-collision, and irreversibility, they cannot certify that the bookkeeper is exactly the worker. Thereafter, such insistence may lead to abuse or even embezzlement of computing power for the benefit of malicious miners. To preserve the functionality of PoW but also bind the miners’ signing keys with their works, we build a post-quantum PoW scheme by changing the approximate closest vector norm for… More >

Gang Xu¹, Rui-Ting Shan², Xiu-Bo Chen², Mianxiong Dong³, Yu-Ling Chen^4,*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 339-349, 2021, DOI:10.32604/cmc.2021.017968

Abstract With the emergence of classical communication security problems, quantum communication has been studied more extensively. In this paper, a novel probabilistic hierarchical quantum information splitting protocol is designed by using a non-maximally entangled four-qubit cluster state. Firstly, the sender Alice splits and teleports an arbitrary one-qubit secret state invisibly to three remote agents Bob, Charlie, and David. One agent David is in high grade, the other two agents Bob and Charlie are in low grade. Secondly, the receiver in high grade needs the assistance of one agent in low grade, while the receiver in low grade needs the aid of… More >

Naiwei Lu^1,*, Honghao Wang¹, Kai Wang¹, Yang Liu²

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 345-360, 2021, DOI:10.32604/cmes.2021.013792

Abstract The steadily growing traffic load has resulted in lots of bridge collapse events over the past decades, especially for short-to-medium span bridges. This study investigated probabilistic and dynamic traffic load effects on short-to-medium span bridges using practical heavy traffic data in China. Mathematical formulations for traffic-bridge coupled vibration and probabilistic extrapolation were derived. A framework for extrapolating probabilistic and dynamic traffic load effect was presented to conduct an efficient and accurate extrapolation. An equivalent dynamic wheel load model was demonstrated to be feasible for short-to-medium span bridges. Numerical studies of two types of simply-supported bridges were conducted based on site-specific… More >

Lu Li¹, Yuzhen Fan², Xinglang Su^1,*, Gefei Qiu¹

Energy Engineering, Vol.118, No.3, pp. 565-580, 2021, DOI:10.32604/EE.2021.014627

Abstract Because of the randomness and uncertainty, integration of large-scale wind farms in a power system will exert significant influences on the distribution of power flow. This paper uses polynomial normal transformation method to deal with non-normal random variable correlation, and solves probabilistic load flow based on Kriging method. This method is a kind of smallest unbiased variance estimation method which estimates unknown information via employing a point within the confidence scope of weighted linear combination. Compared with traditional approaches which need a greater number of calculation times, long simulation time, and large memory space, Kriging method can rapidly estimate node… More >

Gundala Swathi^*

Computer Systems Science and Engineering, Vol.35, No.5, pp. 335-345, 2020, DOI:10.32604/csse.2020.35.335

Abstract Researches in wireless mobile ad hoc networks have an inherent challenge of vulnerable diagnosis due to the diverse behaviour pattern of the vulnerable nodes causing heterogeneous vtype1, vtype2, vtupe3 and vtype4 faults. This paper proposes a protocol for the diagnosis of vulnerability nodes with threephases of clustering, vulnerable detection and vulnerable fault classification in wireless networks. This protocol employs the technique of probabilistic neural network for classification of vulnerable nodes and detects vulnerable nodes through timeout mechanism and vtype3, vtype4, vtype1, vtype2 nodes through the method of analysis variance. Network simulator NS-2.3.35 is employed for performance evaluation of the protocol. More >

Jiaqi He¹, Yangjun Luo^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 777-800, 2020, DOI:10.32604/cmes.2020.010688

Abstract For structures that only the predicted bounds of uncertainties are available, this study proposes a Bayesian method to logically evaluate the nonprobabilistic reliability of structures based on multi-ellipsoid convex model and performance test data. According to the given interval ranges of uncertainties, we determine the initial characteristic parameters of a multi-ellipsoid convex set. Moreover, to update the plausibility of characteristic parameters, a Bayesian network for the information fusion of prior uncertainty knowledge and subsequent performance test data is constructed. Then, an updated multi-ellipsoid set with the maximum likelihood of the performance test data can be achieved. The credible non-probabilistic reliability… More >