Emna Karray¹, Hela Elmannai^2,*, Elyes Toumi¹, Mohamed Hedi Gharbia³, Souham Meshoul², Hamouda Aichi⁴, Zouhaier Ben Rabah¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1399-1425, 2023, DOI:10.32604/cmes.2023.023164 - 06 February 2023

Abstract Pedo-spectroscopy has the potential to provide valuable information about soil physical, chemical, and biological properties. Nowadays, we may predict soil properties using VNIR field imaging spectra (IS) such as Prisma satellite data or laboratory spectra (LS). The primary goal of this study is to investigate machine learning models namely Partial Least Squares Regression (PLSR) and Support Vector Regression (SVR) for the prediction of several soil properties, including clay, sand, silt, organic matter, nitrate NO3-, and calcium carbonate CaCO3, using five VNIR spectra dataset combinations (% IS, % LS) as follows: C1 (0% IS, 100% LS),… More > Graphic Abstract

Wazir Muhammad¹, Zuhaibuddin Bhutto^2,*, Salman Masroor^3,4, Murtaza Hussain Shaikh⁵, Jalal Shah², Ayaz Hussain¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1121-1142, 2023, DOI:10.32604/cmes.2023.021438 - 06 February 2023

Abstract Medical image super-resolution is a fundamental challenge due to absorption and scattering in tissues. These challenges are increasing the interest in the quality of medical images. Recent research has proven that the rapid progress in convolutional neural networks (CNNs) has achieved superior performance in the area of medical image super-resolution. However, the traditional CNN approaches use interpolation techniques as a preprocessing stage to enlarge low-resolution magnetic resonance (MR) images, adding extra noise in the models and more memory consumption. Furthermore, conventional deep CNN approaches used layers in series-wise connection to create the deeper mode, because More >

Wenchuan Wang^1,*, Weican Tian¹, Kwok-wing Chau², Yiming Xue¹, Lei Xu³, Hongfei Zang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1603-1642, 2023, DOI:10.32604/cmes.2023.026231 - 06 February 2023

Abstract The Bald Eagle Search algorithm (BES) is an emerging meta-heuristic algorithm. The algorithm simulates the hunting behavior of eagles, and obtains an optimal solution through three stages, namely selection stage, search stage and swooping stage. However, BES tends to drop-in local optimization and the maximum value of search space needs to be improved. To fill this research gap, we propose an improved bald eagle algorithm (CABES) that integrates Cauchy mutation and adaptive optimization to improve the performance of BES from local optima. Firstly, CABES introduces the Cauchy mutation strategy to adjust the step size of… More >

Ruijun Liu¹, Haisheng Li^1,*, Zhihan Lv²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 985-1022, 2023, DOI:10.32604/cmes.2023.023154 - 06 February 2023

Abstract To understand the current application and development of 3D modeling in Digital Twins (DTs), abundant literatures on DTs and 3D modeling are investigated by means of literature review. The transition process from 3D modeling to DTs modeling is analyzed, as well as the current application of DTs modeling in various industries. The application of 3D DTs modeling in the fields of smart manufacturing, smart ecology, smart transportation, and smart buildings in smart cities is analyzed in detail, and the current limitations are summarized. It is found that the 3D modeling technology in DTs has broad More >

Pavel Trojovský^1,*, Mohammad Dehghani¹, Eva Trojovská¹, Eva Milkova²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1527-1573, 2023, DOI:10.32604/cmes.2023.025908 - 06 February 2023

Abstract In this paper, based on the concept of the NFL theorem, that there is no unique algorithm that has the best performance for all optimization problems, a new human-based metaheuristic algorithm called Language Education Optimization (LEO) is introduced, which is used to solve optimization problems. LEO is inspired by the foreign language education process in which a language teacher trains the students of language schools in the desired language skills and rules. LEO is mathematically modeled in three phases: (i) students selecting their teacher, (ii) students learning from each other, and (iii) individual practice, considering… More > Graphic Abstract

Zheng Liu^*, Wei Xiong, Minghui Xiong

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1143-1163, 2023, DOI:10.32604/cmes.2023.025452 - 06 February 2023

Abstract This study investigates the scheduling problem of multiple agile optical satellites with large-scale tasks. This problem is difficult to solve owing to the time-dependent characteristic of agile optical satellites, complex constraints, and considerable solution space. To solve the problem, we propose a scheduling method based on an improved sine and cosine algorithm and a task merging approach. We first establish a scheduling model with task merging constraints and observation action constraints to describe the problem. Then, an improved sine and cosine algorithm is proposed to search for the optimal solution with the maximum profit ratio. More >

Saifur Rahman Sabuj¹, Mohammad Saadman Alam², Majumder Haider², Md Akbar Hossain³, Al-Sakib Khan Pathan^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1053-1089, 2023, DOI:10.32604/cmes.2023.024078 - 06 February 2023

Abstract This paper discusses the significance and prospects of low altitude small satellite aerial vehicles to ensure smooth aerial-ground communications for next-generation broadband networks. To achieve the generic goals of fifthgeneration and beyond wireless networks, the existing aerial network architecture needs to be revisited. The detailed architecture of low altitude aerial networks and the challenges in resource management have been illustrated in this paper. Moreover, we have studied the coordination between promising communication technologies and low altitude aerial networks to provide robust network coverage. We talk about the techniques that can ensure userfriendly control and monitoring More > Graphic Abstract

Christophe Chesneau^1,*, Hassan Doosti²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 981-983, 2023, DOI:10.32604/cmes.2023.028283 - 06 February 2023

Abstract This article has no abstract. More >

Miaomiao Yang^1,2, Guosheng Huang^1,2, Junwei Liu³, Yanshuang Gui^1,2, Qixu Wang^1,2,*, Xingshu Chen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1879-1898, 2023, DOI:10.32604/cmes.2023.026371 - 06 February 2023

Abstract With the advantages of lightweight and high resource utilization, cloud-native technology with containers as the core is gradually becoming the mainstream technical architecture for information infrastructure. However, malware attacks such as Doki and Symbiote threaten the container runtime’s security. Malware initiates various types of runtime anomalies based on process form (e.g., modifying the process of a container, and opening the external ports). Fortunately, dynamic monitoring mechanisms have proven to be a feasible solution for verifying the trusted state of containers at runtime. Nevertheless, the current routine dynamic monitoring mechanisms for baseline data protection are still… More >

Yingxue Sang¹, Fengxia Han^1,2,*, Qing Liu^1,2, Liang Qiao³, Shouxi Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1973-1998, 2023, DOI:10.32604/cmes.2023.026218 - 06 February 2023

Abstract Rapid urbanization has led to a surge in the number of towering structures, and overturning is widely used because it can better accommodate the construction of shaped structures such as variable sections. The complexity of the construction process makes the construction risk have certain randomness, so this paper proposes a cloud-based coupled matter-element model to address the ambiguity and randomness in the safety risk assessment of overturning construction of towering structures. In the pretended model, the digital eigenvalues of the cloud model are used to replace the eigenvalues in the matter–element basic element, and calculate… More >