Y. A. Amer¹, A. T. EL-Sayed², M. N. Abd EL-Salam^3,*

Sound & Vibration, Vol.56, No.2, pp. 89-104, 2022, DOI:10.32604/sv.2022.011838

Abstract In our consideration, a comparison between four different types of controllers for suppression the vibrations of the cantilever beam excited by an external force is carried out. Those four types are the linear velocity feedback control, the cubic velocity feedback control, the non-linear saturation controller (NSC) and the positive position feedback (PPF) controller. The suitable type is the PPF controller for suppression the vibrations of the cantilever beam. The approximate solution obtained up to the first approximation by using the multiple scale method. The PPF controller effectiveness is studied on the system. We used frequency-response equations to investigate the stability… More >

Huading Ling¹, Aiping Zhang¹, Changchun Yin¹, Dafang Li^2,*, Mengyu Chang³

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1561-1577, 2022, DOI:10.32604/iasc.2022.027349

Abstract With the rise of deep learning in recent years, many code clone detection (CCD) methods use deep learning techniques and achieve promising results, so is cross-language CCD. However, deep learning techniques require a dataset to train the models. The dataset is typically small and has a gap between real-world clones due to the difficulty of collecting datasets for cross-language CCD. This creates a data bottleneck problem: data scale and quality issues will cause that model with a better design can still not reach its full potential. To mitigate this, we propose a tree autoencoder (TAE) architecture. It uses unsupervised learning… More >

Xiaosha Qi¹, Genlin Ji^2,*, Jie Zhang², Bo Sheng³

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1861-1875, 2022, DOI:10.32604/iasc.2022.027182

Abstract Video anomaly detection is essential to distinguish abnormal events in large volumes of surveillance video and can benefit many fields such as traffic management, public security and failure detection. However, traditional video anomaly detection methods are unable to accurately detect and locate abnormal events in real scenarios, while existing deep learning methods are likely to omit important information when extracting features. In order to avoid omitting important features and improve the accuracy of abnormal event detection and localization, this paper proposes a novel method called Multi Chunk Learning based Skip Connected Convolutional Auto Encoder (MCSCAE). The proposed method improves the… More >

Tao Zhang^1,*, Yi Cao²

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1677-1685, 2022, DOI:10.32604/iasc.2022.027082

Abstract The images generated by the image stitching algorithm have false shadow and poor real-time performance, and are difficult to maintain visual consistency. For this reason, a panoramic image stitching algorithm based on genetic algorithm is proposed. First, the oriented fast and rotated brief (ORB) algorithm is used to quickly perform detection and description of feature, then the initial feature point pairs are extracted according to the Euclidean distance for feature point rough matching, the parallelism of genetic algorithm is used to optimize the feature point matching performance. Finally, the PROSAC algorithm is used to remove mismatched point pairs and get… More >

Xiaona Hu^1,2, Baiqing Zhou^1,*, Jinyue Xia³, Yao Chen⁴, Gang Hu⁵

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1801-1813, 2022, DOI:10.32604/iasc.2022.027034

Abstract With the global warming to the survival and development of mankind, more and more attention is paid to low-carbon, green and energy-saving production. As one of the main modes of international transportation, the wharf has been facing a serious problem of its high carbon-emission. In order to balance the relationship between port energy consumption and efficiency, it is necessary to study the berth allocation, loading and unloading of bulk terminal from the perspective of energy saving with the proposal of energy saving and emission reduction in China. Both energy saving and efficiency can be achieved at the bulk terminal in… More >

Jun Zhu^1,*, Chaosong Yan², Yinglong Ouyang³, Yao Chen⁴, Xiaowan Wang⁵

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1747-1756, 2022, DOI:10.32604/iasc.2022.026934

Abstract The shipbuilding industry has problems such as long transaction cycles, many participating suppliers, and data sensitivity. A time-dimensional shipbuilding information security sharing scheme based on an alliance chain is proposed to solve this problem. The blockchain can better deliver value and protect user privacy, the blockchain can directly complete the instant transfer of value through smart contracts and tokens on the blockchain. We divide the program into three parts: data preprocessing, data storage, and data sharing. For data sensitivity, data confidentiality and reliability are handled separately. Aiming at the problem of user privacy leakage in data storage, a privacy-protecting blockchain… More >

Ruhao Ma^1,*, Fansheng Meng¹, Haiwen Du^2,3

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1623-1637, 2022, DOI:10.32604/iasc.2022.026748

Abstract Blockchain technology ensures the security of cross-organizational data sharing in the process of collaborative innovation. It drives the development of collaborative innovation in discrete manufacturing to intelligent innovation. However, collaborative innovation is a multi-role, networked, and open resource-sharing process. Therefore, it is easy to form information barriers and increase the risk of cooperation between organizations. In this paper, we firstly analyze the blockchain-based information management models in the traditional discrete manufacturing collaborative innovation process. Then, we found that in the process of industry-university-research (IUR) collaborative innovation, consensus servers maintain too many connections due to the high latency between them, which… More >

Yuhao Chen¹, Jiajun Liu¹, Yaxi Peng¹, Ziyi Liu², Zhipeng Yang^1,*

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1501-1516, 2022, DOI:10.32604/iasc.2022.026346

Abstract As a neural fingerprint, functional connectivity networks (FCNs) have been used to identify subjects from group. However, a number of studies have only paid attention to cerebral cortex when constructing the brain FCN. Other areas of the brain also play important roles in brain activities. It is widely accepted that the human brain is composed of many highly complex functional networks of cortex. Moreover, recent studies have confirmed correlations between signals of cortex and white matter (WM) bundles. Therefore, it is difficult to reflect the functional characteristics of the brain through a single-layer FCN. In this paper, a multilayer FCN… More >

Yu Ren¹, Jiaohua Qin^1,*, Yun Tan¹, Neal N. Xiong²

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1439-1453, 2022, DOI:10.32604/iasc.2022.025485

Abstract In the field of reversible data hiding in encrypted images (RDH-EI), predict an image effectively and embed a message into the image with lower distortion are two crucial aspects. However, due to the linear regression prediction being sensitive to outliers, it is a challenge to improve the accuracy of predictions. To address this problem, this paper proposes an RDH-EI scheme based on adaptive prediction-error label map. In the prediction stage, an adaptive threshold estimation algorithm based on local complexity is proposed. Then, the pixels selection method based on gradient of image is designed to train the parameters of the prediction… More >

S. Vimal¹, S. Nalini^2,*, K. Anguraj³, T. Chelladurai⁴

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1907-1921, 2022, DOI:10.32604/iasc.2022.025219

Abstract Recent advancements in hardware and networking technologies have resulted in a large growth in the number of Internet of Things (IoT) devices connected to the Internet, which is likely to continue growing in the coming years. Traditional security solutions are insufficiently suited to the IoT context due to the restrictions and diversity of the resources available to objects. Security techniques such as intrusion detection and authentication are considered to be effective. Additionally, the decentralised and distributed nature of Blockchain technology makes it an excellent solution for overcoming the security issue. This paper proposes a chaotic bird swarm algorithm (CBSA)-based clustering… More >