Yang Zhang¹, Liru Qiu², Yongkai Zhu¹, Long Wen^1,*, Xiaoping Luo^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 873-894, 2022, DOI:10.32604/cmes.2022.022322

Abstract Pneumonia is part of the main diseases causing the death of children. It is generally diagnosed through chest X-ray images. With the development of Deep Learning (DL), the diagnosis of pneumonia based on DL has received extensive attention. However, due to the small difference between pneumonia and normal images, the performance of DL methods could be improved. This research proposes a new fine-grained Convolutional Neural Network (CNN) for children’s pneumonia diagnosis (FG-CPD). Firstly, the fine-grained CNN classification which can handle the slight difference in images is investigated. To obtain the raw images from the real-world chest X-ray data, the YOLOv4… More >

Chien-Wen Lin¹, Jen-Cheng Wang², Bo-Yan Zhong³, Joe-Air Jiang^4,5, Ya-Fen Wu⁶, Shao-Wei Leu¹, Tzer-En Nee^3,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 619-638, 2022, DOI:10.32604/cmes.2022.021324

Abstract The invariant metrics of the effects of park size and distance to public transportation on housing value volatilities in Boston, Milwaukee, Taipei and Tokyo are investigated. They reveal a Cobb-Douglas-like behavior. The scale-invariant exponents corresponding to the percentage of a green area (a) are 7.4, 8.41, 14.1 and 15.5 for Boston, Milwaukee, Taipei and Tokyo, respectively, while the corresponding direct distances to the nearest metro station (d) are −5, −5.88, −10 and −10, for Boston, Milwaukee, Taipei and Tokyo, respectively. The multiphysics-based analysis provides a powerful approach for the symmetry characterization of market engineering. The scaling exponent ratio between park… More >

João Pedro Ceniz, Rodrigo de Sá Martins, Marco Antonio Luersen^*, Tiago Cousseau

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 601-618, 2022, DOI:10.32604/cmes.2022.021011

Abstract Ore conveyor belt rollers operate in harsh environments, making them prone to premature failure. Their service lives are highly dependent on the stress field and bearing misalignment angle, for which limit values are defined in a standard. In this work, an optimization methodology using metamodels based on radial basis functions is implemented to reduce the mass of two models of rollers. From a structural point of view, one of the rollers is made completely of metal, while the other also has some components made of polymeric material. The objective of this study is to develop and apply a parametric structural… More >

Hye Kyung Kim^1,*, Dae Sik Lee²

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 825-842, 2022, DOI:10.32604/cmes.2022.022103

Abstract The generating functions of special numbers and polynomials have various applications in many fields as well as mathematics and physics. In recent years, some mathematicians have studied degenerate version of them and obtained many interesting results. With this in mind, in this paper, we introduce the degenerate r-Dowling polynomials and numbers associated with the degenerate r-Whitney numbers of the second kind. We derive many interesting properties and identities for them including generating functions, Dobinski-like formula, integral representations, recurrence relations, differential equation and various explicit expressions. In addition, we explore some expressions for them that can be derived from repeated applications… More >

Zida Liu¹, Danial Jahed Armaghani^2,*, Pouyan Fakharian³, Diyuan Li⁴, Dmitrii Vladimirovich Ulrikh⁵, Natalia Nikolaevna Orekhova⁶, Khaled Mohamed Khedher^7,8

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 799-824, 2022, DOI:10.32604/cmes.2022.021165

Abstract The uniaxial compressive strength (UCS) of rock is an essential property of rock material in different relevant applications, such as rock slope, tunnel construction, and foundation. It takes enormous time and effort to obtain the UCS values directly in the laboratory. Accordingly, an indirect determination of UCS through conducting several rock index tests that are easy and fast to carry out is of interest and importance. This study presents powerful boosting trees evaluation framework, i.e., adaptive boosting machine, extreme gradient boosting machine (XGBoost), and category gradient boosting machine, for estimating the UCS of sandstone. Schmidt hammer rebound number, P-wave velocity,… More >

Osman Zeki Okuyucu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 653-671, 2022, DOI:10.32604/cmes.2022.021081

Abstract In this study, we examine the possible relations between the Frenet planes of any given two curves in three dimensional Lie groups with left invariant metrics. We explain these possible relations in nine cases and then introduce the conditions that must be met to coincide with the planes of these curves in nine theorems. More >

Omar Said^*

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 673-695, 2022, DOI:10.32604/cmes.2022.021160

Abstract In recent years, the Internet of Things (IoT) technology has been considered one of the most attractive fields for researchers due to its aspirations and implications for society and life as a whole. The IoT environment contains vast numbers of devices, equipment, and heterogeneous users who generate massive amounts of data. Furthermore, things’ entry into and exit from IoT systems occur dynamically, changing the topology and content of IoT networks very quickly. Therefore, managing IoT environments is among the most pressing challenges. This paper proposes an adaptive and dynamic scheme for managing IoT environments is proposed. This management scheme depends… More >

Nilkanth Mukund Deshpande^1,2, Shilpa Gite^6,7,*, Biswajeet Pradhan^3,4,5, Mazen Ebraheem Assiri⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 843-872, 2022, DOI:10.32604/cmes.2022.021225

Abstract Machine learning (ML) has emerged as a critical enabling tool in the sciences and industry in recent years. Today’s machine learning algorithms can achieve outstanding performance on an expanding variety of complex tasks–thanks to advancements in technique, the availability of enormous databases, and improved computing power. Deep learning models are at the forefront of this advancement. However, because of their nested nonlinear structure, these strong models are termed as “black boxes,” as they provide no information about how they arrive at their conclusions. Such a lack of transparencies may be unacceptable in many applications, such as the medical domain. A… More >

Tomás Sureda Riera^1,*, Juan Ramón Bermejo Higuera², Javier Bermejo Higuera², Juan Antonio Sicilia Montalvo², José Javier Martínez Herráiz¹

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 579-599, 2022, DOI:10.32604/cmes.2022.020976

Abstract Web applications represent one of the principal vehicles by which attackers gain access to an organization’s network or resources. Thus, different approaches to protect web applications have been proposed to date. Of them, the two major approaches areWeb Application Firewalls (WAF) and Runtime Application Self Protection (RASP). It is, thus, essential to understand the differences and relative effectiveness of both these approaches for effective decisionmaking regarding the security of web applications. Here we present a comparative study between WAF and RASP simulated settings, with the aim to compare their effectiveness and efficiency against different categories of attacks. For this, we… More >

Francesco Tornabene^*, Matteo Viscoti, Rossana Dimitri

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 719-798, 2022, DOI:10.32604/cmes.2022.022210

Abstract The article proposes an Equivalent Single Layer (ESL) formulation for the linear static analysis of arbitrarily-shaped shell structures subjected to general surface loads and boundary conditions. A parametrization of the physical domain is provided by employing a set of curvilinear principal coordinates. The generalized blending methodology accounts for a distortion of the structure so that disparate geometries can be considered. Each layer of the stacking sequence has an arbitrary orientation and is modelled as a generally anisotropic continuum. In addition, re-entrant auxetic three-dimensional honeycomb cells with soft-core behaviour are considered in the model. The unknown variables are described employing a… More > Graphic Abstract