Lianghao Hua^1,2, Jianfeng Zhang^1,*, Dejie Li³, Xiaobo Xi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2129-2157, 2024, DOI:10.32604/cmes.2023.030535

Abstract With the increasing prevalence of high-order systems in engineering applications, these systems often exhibit significant disturbances and can be challenging to model accurately. As a result, the active disturbance rejection controller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmanned aerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances and the possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address these issues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neural network (RBFNN) with a second-order ADRC and leverages a… More > Graphic Abstract

Mohamed Zarouan¹, Ibrahim M. Mehedi^1,2,*, Shaikh Abdul Latif³, Md. Masud Rana⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1341-1364, 2024, DOI:10.32604/cmes.2023.030037

Abstract Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamless operation of the system. Current industrial processes are getting smarter with the emergence of Industry 4.0. Specifically, various modernized industrial processes have been equipped with quite a few sensors to collect process-based data to find faults arising or prevailing in processes along with monitoring the status of processes. Fault diagnosis of rotating machines serves a main role in the engineering field and industrial production. Due to the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experience and human knowledge, intellectual… More >

Chia-Wei Jan¹, Yu-Jhih Chiu¹, Kuan-Lin Chen², Ting-Chun Yao³, Ping-Huan Kuo^1,4,*

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2989-3010, 2023, DOI:10.32604/csse.2023.042078

Abstract Pneumonia is a common lung disease that is more prone to affect the elderly and those with weaker respiratory systems. However, hospital medical resources are limited, and sometimes the workload of physicians is too high, which can affect their judgment. Therefore, a good medical assistance system is of great significance for improving the quality of medical care. This study proposed an integrated system by combining transfer learning and gradient-weighted class activation mapping (Grad-CAM). Pneumonia is a common lung disease that is generally diagnosed using X-rays. However, in areas with limited medical resources, a shortage of medical personnel may result in… More >

Firas Abedi¹, Hayder M. A. Ghanimi², Abeer D. Algarni³, Naglaa F. Soliman^3,*, Walid El-Shafai^4,5, Ali Hashim Abbas⁶, Zahraa H. Kareem⁷, Hussein Muhi Hariz⁸, Ahmed Alkhayyat⁹

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2791-2814, 2023, DOI:10.32604/csse.2023.038762

Abstract Data mining plays a crucial role in extracting meaningful knowledge from large-scale data repositories, such as data warehouses and databases. Association rule mining, a fundamental process in data mining, involves discovering correlations, patterns, and causal structures within datasets. In the healthcare domain, association rules offer valuable opportunities for building knowledge bases, enabling intelligent diagnoses, and extracting invaluable information rapidly. This paper presents a novel approach called the Machine Learning based Association Rule Mining and Classification for Healthcare Data Management System (MLARMC-HDMS). The MLARMC-HDMS technique integrates classification and association rule mining (ARM) processes. Initially, the chimp optimization algorithm-based feature selection (COAFS)… More >

Asma A. Alhashmi¹, Abdulbasit A. Darem^1,*, Sultan M. Alanazi¹, Abdullah M. Alashjaee², Bader Aldughayfiq³, Fuad A. Ghaleb^4,5, Shouki A. Ebad¹, Majed A. Alanazi¹

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3483-3498, 2023, DOI:10.32604/cmc.2023.041038

Abstract In an era marked by escalating cybersecurity threats, our study addresses the challenge of malware variant detection, a significant concern for a multitude of sectors including petroleum and mining organizations. This paper presents an innovative Application Programmable Interface (API)-based hybrid model designed to enhance the detection performance of malware variants. This model integrates eXtreme Gradient Boosting (XGBoost) and an Artificial Neural Network (ANN) classifier, offering a potent response to the sophisticated evasion and obfuscation techniques frequently deployed by malware authors. The model’s design capitalizes on the benefits of both static and dynamic analysis to extract API-based features, providing a holistic… More >

Hongfei Ye^1,*, Chenguang Yin¹, Jian Wang¹, Yonggang Zheng¹, Hongwu Zhang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09741

Abstract The wetting behavior is ubiquitous in natural phenomenon as well as engineering application. As an intrinsic property of solid surface, the wettability with a controllable gradient has been an attractive issue with a wide application in various fields, including microfluidic devices, self-driven transport, biotechnologies, etc. Generally, it often requires elaborate design of microstructure or its response under the electrical, thermal, optical, pH stimuli, etc. However, the relevant complex underlying mechanism makes it difficult to construct quantitative relations between the wettability and the external field for the fine design. In this work, based on the bilayer two-dimensional materials, a simple controlling… More >

Zhiqiang Yang^1,*, Yipeng Rao², Yi Sun¹, Junzhi Cui², Meizhen Xiang^3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09513

Abstract An effective fracture model is established for the brittle materials with periodic distribution of micro-cracks using the second-order multiscale asymptotic methods. The main features of the model are: (i) the secondorder strain gradient included in the fracture criterions and (ii) the strain energy and the Griffith criterions for micro-crack extensions established by the multiscale asymptotic expansions. Finally, the accuracy of the presented model is verified by the experiment data and some typical fracture problems. These results illustrate that the second-order fracture model is effective for analyzing the brittle materials with periodic distribution of micro-cracks. More >

Dongze Yan¹, Jianxiang Wang², Lihua Shao^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09357

Abstract Non-uniform strains produce a localized break in the microscopic inverse symmetry of materials, which leads to the electromechanical coupling phenomenon known as flexoelectricity in all dielectric materials. However, the size-dependent flexoelectric effect typically only manifests at small scales. Creating a considerable flexoelectric output at the macroscopic scale remains a bottleneck. Micro- and nano-porous materials own a significant number of randomly distributed microscopic pores and ligamentous structures, which can deform non-uniformly under arbitrary forms of macroscopic loading. Moreover, since the small size effect of flexoelectricity, the entire flexoelectricity of the micro- and nano-porous materials will be much more significant than that… More >

Nizar Faisal Alkayem¹, Maosen Cao^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09367

Abstract Structural damage identification is a key engineering technique that attempts to ensure structural reliability. In this regard, one of the major intelligent approaches is the inverse analysis of structural damage using metaheuristics. By considering the recent achievements, an efficient hybrid objective function that combines the modal kinetic energy and modal strain energy is developed. The objective function aims to extract maximum modal information from the structure and overcome noisy conditions. Moreover, the original methods are usually vulnerable to the associated high multimodality and uncertainty of the inverse problem. Therefore, the particle swarm algorithm (PSO) mechanism is combined with another newly… More >

Guo Li¹, Shaochen Bao², Shuiting Ding³, Zhenlei Li^2,*, Liangliang Zuo¹, Shuyang Xia¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09927

Abstract Advanced air-cooling turbine blades are capable of operating above the melting temperature of Nickel-based superalloy, which accordingly withstand complex thermomechanical fatigue loads during service life. This paper considers the problem of realizing gas turbine representative thermal gradients in the elevated temperature fatigue test, while ensuring the thermal gradient induced stress inside the specimens. For this purpose, a novel temperature control device utilizing impingement cooling, which supplies cooling air inside the gauge section and releases toward the inner wall, was constructed in tubular fatigue specimens. A single induction coil was arranged outside the gauge section, providing heat sources to establish thermal… More >