Samayan Narayanamoorthy¹, Arumugam Anuja¹, J. V. Brainy¹, Thangaraj Manirathinam¹, Subramaniam Pragathi¹, Thirumalai Nallasivan Parthasarathy¹, Daekook Kang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1229-1261, 2022, DOI:10.32604/cmes.2022.019442

Abstract As the quantity of garbage created every day rises, solid waste management has become the world’s most important issue. As a result, improper solid waste disposal and major sanitary issues develop, which are only detected after they have become dangerous. Due to the system’s lockdown during the COVID-19 pandemic, this scenario became much more uncertain. We are at the stage to develop and execute effective waste management procedures, as well as long-term policies and forward-thinking programmes that can work even in the most adverse of scenarios. We incorporate major solid waste (organic and inorganic solid wastes) approaches that actually perform… More >

Siyuan Mei^1,2, Yingyi Chen^1,2,*, Hanxiang Qin^1,2, Huihui Yu³, Daoliang Li^1,2, Boyang Sun^1,2, Ling Yang^1,2, Yeqi Liu^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1315-1335, 2022, DOI:10.32604/cmes.2022.019378

Abstract Fish behavior analysis for recognizing stress is very important for fish welfare and production management in aquaculture. Recent advances have been made in fish behavior analysis based on deep learning. However, most existing methods with top performance rely on considerable memory and computational resources, which is impractical in the real-world scenario. In order to overcome the limitations of these methods, a new method based on knowledge distillation is proposed to identify the stress states of fish schools. The knowledge distillation architecture transfers additional inter-class information via a mixed relative loss function, and it forces a lightweight network (GhostNet) to mimic… More >

Yiping Sun^1,2, Jiadui Chen¹, Qiang Bai¹, Xuefeng Zhao¹, Meng Tao^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1693-1716, 2022, DOI:10.32604/cmes.2022.019336

Abstract Research on the acoustic performance of an anechoic coating composed of cavities in a viscoelastic material has recently become an area of great interest. Traditional forward research methods are unable to manipulate sound waves accurately and effectively, are difficult to analyse, have time-consuming solution processes, and have large optimization search spaces. To address these issues, this paper proposes a deep learning-based inverse research method to efficiently invert the material parameters of Alberich-type sound absorption coatings and rapidly predict their acoustic performance. First, an autoencoder (AE) model is pretrained to reconstruct the viscoelastic material parameters of an Alberich-type sound absorption coating,… More >

Bingfei Liu^1,*, Yangjie Hao²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1601-1613, 2022, DOI:10.32604/cmes.2022.019226

Abstract By adding copper to increase the performance, the Ni-Ti-Cu Shape Memory Alloy (SMA), has been widely used in the field of engineering in recent years. A thermodynamic constitutive model for Ni-Ti-Cu SMA considering different copper contents is established in this work. Numerical results for two different copper contents, as examples, are compared with the experimental results to verify the accuracy of the theoretical work. Based on the verified constitutive model, the effects of different copper content on the mechanical properties of Ni-Ti-Cu SMA and the tensile and compressive asymmetric properties of Ni-Ti-Cu SMA are finally discussed, respectively. More >

Duansen Shangguan^*, Liping Chen, Chang Su, Jianwan Ding, Chan Liu

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1557-1578, 2022, DOI:10.32604/cmes.2022.018979

Abstract With the development of information and communication technology and the advent of the Internet of Things (IoT) era, cyber-physical system (CPS) is becoming the trend of products or systems. The deep integration and real-time interaction between the physical world and the virtual world expand system functions. Although there are some CPS implementation guidelines, the virtual world is still relatively abstract compared to the concrete physical world that can be touched through the IoT. Besides that, human is a non-negligible CPS endogenous interactive intelligent component. In this paper, we propose a triple human-digital twin architecture, where the physical objects and the… More >

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 >