Fang Zhao¹, Dongming Xiang^2,*, Guanjun Liu¹, Changjun Jiang¹, Honghao Zhu³

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1337-1363, 2022, DOI:10.32604/cmes.2022.018872

Abstract Workflow system has become a standard solution for managing a complex business process. How to guarantee its correctness is a key requirement. Many methods only focus on the control-flow verification, while they neglect the modeling and checking of data-flows. Although some studies are presented to repair the data-flow errors, they do not consider the effect of delete operations or weak circulation relations on the repairing results. What's more, repairing some data-flow errors may bring in new errors. In order to solve these problems, we use workflow net with data (WFD-net) systems to model and analyze a workflow system. Based on… More >

Hongyun Jiao¹, Mi Zhao¹, Jingqi Huang^2,*, Xu Zhao^1,3, Xiuli Du¹

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1289-1314, 2022, DOI:10.32604/cmes.2022.018540

Abstract Tunnel portal sections often suffer serious damage in strong earthquake events. Earthquake waves may propagate in different directions, producing various dynamic responses in the tunnel portal. Based on the Galongla tunnel, which is located in a seismic region of China, three-dimensional seismic analysis is conducted to investigate the dynamic response of a tunnel portal subjected to earthquake waves with different vibration directions. In order to simulate the mechanic behavior of slope rock effectively, an elastoplastic damage model is adopted and applied to ABAQUS software by a self-compiled user material (UMAT) subroutine. Moreover, the seismic wave input method for tunnel portal… More >

Wenwen Zhou, Mengyao Chen, Yang Gao^*, Ruilin Feng

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1635-1652, 2022, DOI:10.32604/cmes.2022.018437

Abstract To avoid the effects of systemic financial risks caused by extreme fluctuations in housing price, the Chinese government has been exploring the most effective policies for regulating the housing market. Measuring the effect of real estate regulation policies has been a challenge for present studies. This study innovatively employs big data technology to obtain Internet search data (ISD) and construct market concern index (MCI) of policy, and hedonic price theory to construct hedonic price index (HPI) based on building area, age, ring number, and other hedonic variables. Then, the impact of market concerns for restrictive policy, monetary policy, fiscal policy,… More >

Wael Alosaimi^1,*, M. Irfan Uddin²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1387-1401, 2022, DOI:10.32604/cmes.2022.018433

Abstract Deep Learning (DL) techniques as a subfield of data science are getting overwhelming attention mainly because of their ability to understand the underlying pattern of data in making classifications. These techniques require a considerable amount of data to efficiently train the DL models. Generally, when the data size is larger, the DL models perform better. However, it is not possible to have a considerable amount of data in different domains such as healthcare. In healthcare, it is impossible to have a substantial amount of data to solve medical problems using Artificial Intelligence, mainly due to ethical issues and the privacy… More >

Gang Xu^1,2, Fan Yun¹, Xiu-Bo Chen^3,*, Shiyuan Xu¹, Jingzhong Wang¹, Tao Shang⁴, Yan Chang⁵, Mianxiong Dong⁶

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 531-541, 2022, DOI:10.32604/iasc.2022.028264

Abstract Secure multi-party computation has been playing a fundamental role in terms of classical cryptography. Quantum homomorphic encryption (QHE) could compute the encrypted data without decryption. At present, most protocols use a semi-honest third party (TP) to protect participants’ secrets. We use a quantum homomorphic encryption scheme instead of TP to protect the privacy of parties. Based on quantum homomorphic encryption, a secure multi-party quantum summation scheme is proposed in which N participants can delegate a server with strong quantum computing power to assist computation. By delegating the computation and key update processes to a server and a semi-honest key center,… More >

Min Rao¹, Yufeng Li^1,*, Hongye Liu², Isabel Wang³, Yongjun Ren⁴

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 455-466, 2022, DOI:10.32604/iasc.2022.027694

Abstract The aim of spinal cord injury rehabilitation is to increase the independent ability of patients, so that patients can return to society and live a creative life. Regaining independence living is the primary goal of rehabilitation. Rehabilitation of patients with spinal cord injury is a long and lengthy process, which needs comprehensive dimensions support from medical workers, family members, and social support. At present, medical institutions and researchers mainly focus on the level of physical recovery and the treatment of complications in patients with spinal cord injury and pay less attention to social factors during the rehabilitation treatment of patients.… More >

Ling Wang¹, Shan Ji², Zhaokang Wang³, Xiaowan Wang^4,*, Ghulam Mohiuddin⁵, Yongjun Ren¹

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 221-234, 2022, DOI:10.32604/iasc.2022.027536

Abstract As the data scale exceeds the petabyte level, more and more users outsource their local databases to third-party service providers to save local storage costs and avoid cumbersome local data management. However, because third-party service providers are not fully trusted, they may leak outsourced data and bring security risks to the personal privacy of data users. The service provider may also return incorrect or incomplete query results to the data user. Therefore, in this paper, we propose a Lightweight and Verifiable Multi-keyword Query Scheme for the integrity verification of multi-keyword query of outsourced data. This scheme supports multi-keyword query integrity… More >

Yintong Wang^1,2,*, Yingjie Yang², Haiyan Chen³, Hao Zheng¹, Heyou Chang¹

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 371-388, 2022, DOI:10.32604/iasc.2022.027146

Abstract Handwritten Chinese recognition which involves variant writing style, thousands of character categories and monotonous data mark process is a long-term focus in the field of pattern recognition research. The existing methods are facing huge challenges including the complex structure of character/line-touching, the discriminate ability of similar characters and the labeling of training datasets. To deal with these challenges, an end-to-end residual attention handwritten Chinese paragraph text recognition method is proposed, which uses fully convolutional neural networks as the main structure of feature extraction and employs connectionist temporal classification as a loss function. The novel residual attention gate block is more… More >

Wei Fang^1,2,*, Yu Sha¹, Meihan Qi¹, Victor S. Sheng³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 609-622, 2022, DOI:10.32604/iasc.2022.027067

Abstract With the rapid development of personalized services, major websites have launched a recommendation module in recent years. This module will recommend information you are interested in based on your viewing history and other information, thereby improving the economic benefits of the website and increasing the number of users. This paper has introduced content-based recommendation algorithm, K-Nearest Neighbor (KNN)-based collaborative filtering (CF) algorithm and singular value decomposition-based (SVD) collaborative filtering algorithm. However, the mentioned recommendation algorithms all recommend for a certain aspect, and do not realize the recommendation of specific movies input by specific users which will cause the recommended content… More >

Rongrong Ni¹, Xiaofeng Liu^1,*, Yizhou Chen¹, Xu Zhou¹, Huili Cai¹, Loo Chu Kiong²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 149-164, 2022, DOI:10.32604/iasc.2022.026813

Abstract Lonely older adults and persons restricted in movements are apt to cause negative emotions, which is harmful to their mental health. A humanoid robot with audiovisual interactions is presented, which can correspondingly output positive facial expressions to relieve human's negative facial expressions. The negative emotions are identified through an attention-enhanced facial expression recognition (FER) network. The network is firstly trained on MMEW macro-and micro-expression databases to discover expression-related features. Then, macro-expression recognition tasks are performed by fine-tuning the trained models on several benchmarking FER databases, including CK+ and Oulu-CASIA. A transformer network is introduced to process the sequential features engineered… More >