Open Access
ARTICLE
Jiayu Ren1,*, Yoshihisa Fujita2, Susumu Nakata2
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2111-2125, 2023, DOI:10.32604/cmes.2023.025970
Abstract Implicit surface generation based on the interpolation of surface points is one of the well-known modeling methods in the area of computer graphics. Several methods for the implicit surface reconstruction from surface points have been proposed on the basis of radial basis functions, a weighted sum of local functions, splines, wavelets, and combinations of them. However, if the surface points contain errors or are sparsely distributed, irregular components, such as curvature-shaped redundant bulges and unexpectedly generated high-frequency components, are commonly seen. This paper presents a framework for restoring irregular components generated on and around surfaces. Users are assumed to specify… More >
Open Access
REVIEW
Ziquan Zhu, Shui-Hua Wang, Yu-Dong Zhang*
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2127-2172, 2023, DOI:10.32604/cmes.2023.025484
（This article belongs to this Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
Abstract Problems: For people all over the world, cancer is one of the most feared diseases. Cancer is one of the major
obstacles to improving life expectancy in countries around the world and one of the biggest causes of death before
the age of 70 in 112 countries. Among all kinds of cancers, breast cancer is the most common cancer for women.
The data showed that female breast cancer had become one of the most common cancers. Aims: A large number of
clinical trials have proved that if breast cancer is diagnosed at an early stage, it could give patients more… More >
Graphic Abstract
Open Access
REVIEW
Jiaqi Shao1,#, Shuwen Chen1,2,3,#,*, Jin Zhou1,#, Huisheng Zhu1, Ziyi Wang1, Mackenzie Brown4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2173-2219, 2023, DOI:10.32604/cmes.2023.025499
（This article belongs to this Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
Abstract As a mainstream research direction in the field of image segmentation, medical image segmentation plays a key role in the quantification of lesions, three-dimensional reconstruction, region of interest extraction and so on. Compared with natural images, medical images have a variety of modes. Besides, the emphasis of information which is conveyed by images of different modes is quite different. Because it is time-consuming and inefficient to manually segment medical images only by professional and experienced doctors. Therefore, large quantities of automated medical image segmentation methods have been developed. However, until now, researchers have not developed a universal method for all… More >
Open Access
ARTICLE
Jipeng Gu1, Weijie Zhang1, Youbing Zhang1,*, Binjie Wang1, Wei Lou2, Mingkang Ye3, Linhai Wang3, Tao Liu4
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2221-2236, 2023, DOI:10.32604/cmes.2023.025396
Abstract An improved fuzzy time series algorithm based on clustering is designed in this paper. The algorithm is successfully applied to short-term load forecasting in the distribution stations. Firstly, the K-means clustering method is used to cluster the data, and the midpoint of two adjacent clustering centers is taken as the dividing point of domain division. On this basis, the data is fuzzed to form a fuzzy time series. Secondly, a high-order fuzzy relation with multiple antecedents is established according to the main measurement indexes of power load, which is used to predict the short-term trend change of load in the… More >
Open Access
ARTICLE
Ying Li1,2, Guanghong Gong1, Dan Wang1, Ni Li1,3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2237-2265, 2023, DOI:10.32604/cmes.2023.025193
Abstract There are two types of methods for image segmentation. One is traditional image processing methods, which are sensitive to details and boundaries, yet fail to recognize semantic information. The other is deep learning methods, which can locate and identify different objects, but boundary identifications are not accurate enough. Both of them cannot generate entire segmentation information. In order to obtain accurate edge detection and semantic information, an Adaptive Boundary and Semantic Composite Segmentation method (ABSCS) is proposed. This method can precisely semantic segment individual objects in large-size aerial images with limited GPU performances. It includes adaptively dividing and modifying the… More >
Graphic Abstract
Open Access
ARTICLE
Abdelazim G. Hussien1,2, Guoxi Liang3, Huiling Chen4,*, Haiping Lin5,*
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2267-2289, 2023, DOI:10.32604/cmes.2023.024247
Abstract Many complex optimization problems in the real world can easily fall into local optimality and fail to find
the optimal solution, so more new techniques and methods are needed to solve such challenges. Metaheuristic
algorithms have received a lot of attention in recent years because of their efficient performance and simple
structure. Sine Cosine Algorithm (SCA) is a recent Metaheuristic algorithm that is based on two trigonometric
functions Sine & Cosine. However, like all other metaheuristic algorithms, SCA has a slow convergence and may
fail in sub-optimal regions. In this study, an enhanced version of SCA named RDSCA is suggested… More >
Open Access
ARTICLE
Abdullah Ahmed Al-Dulaimi1,*, Muhammet Tahir Guneser1, Alaa Ali Hameed2, Mohammad Shukri Salman3
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2291-2319, 2023, DOI:10.32604/cmes.2023.026065
Abstract Recently, the demand for renewable energy has increased due to its environmental and economic needs. Solar
panels are the mainstay for dealing with solar energy and converting it into another form of usable energy. Solar
panels work under suitable climatic conditions that allow the light photons to access the solar cells, as any blocking
of sunlight on these cells causes a halt in the panels work and restricts the carry of these photons. Thus, the panels
are unable to work under these conditions. A layer of snow forms on the solar panels due to snowfall in areas with
low temperatures.… More >
Graphic Abstract
Open Access
ARTICLE
Tareq Alhmiedat1,2,*, Ashraf M. Marei1,2, Saleh Albelwi1,2, Anas Bushnag2, Wassim Messoudi2, Abdelrahman Osman Elfaki2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2321-2344, 2023, DOI:10.32604/cmes.2023.025641
Abstract Agricultural projects in different parts of the world depend on underground water wells. Recently, there have been
many unfortunate incidents in which children have died in abandoned underground wells. Providing topographical
information for these wells is a prerequisite to protecting people from the dangers of falling into them, especially
since most of these wells become buried over time. Many solutions have been developed recently, most with the
aim of exploring these well areas. However, these systems suffer from several limitations, including high complexity,
large size, or inefficiency. This paper focuses on the development of a smart exploration unit that is… More >
Open Access
ARTICLE
Dong Qing1,*, Qi Song1, Shuangyun Huang2, Gening Xu1
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2345-2370, 2023, DOI:10.32604/cmes.2023.026552
Abstract For the randomness of crane working load leading to the decrease of load spectrum prediction accuracy with time,
an adaptive TSSA-HKRVM model for crane load spectrum regression prediction is proposed. The heterogeneous
kernel relevance vector machine model (HKRVM) with comprehensive expression ability is established using
the complementary advantages of various kernel functions. The combination strategy consisting of refraction
reverse learning, golden sine, and Cauchy mutation + logistic chaotic perturbation is introduced to form a
multi-strategy improved sparrow algorithm (TSSA), thus optimizing the relevant parameters of HKRVM. The
adaptive updating mechanism of the heterogeneous kernel RVM model under the multi-strategy improved… More >
Open Access
ARTICLE
Aisha Fayomi1, Christophe Chesneau2,*, Farrukh Jamal3, Ali Algarni1
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2371-2403, 2023, DOI:10.32604/cmes.2023.027000
Abstract In this article, we highlight a new three-parameter heavy-tailed lifetime distribution that aims to extend the
modeling possibilities of the Lomax distribution. It is called the extended Lomax distribution. The considered
distribution naturally appears as the distribution of a transformation of a random variable following the logweighted power distribution recently introduced for percentage or proportion data analysis purposes. As a result,
its cumulative distribution has the same functional basis as that of the Lomax distribution, but with a novel
special logarithmic term depending on several parameters. The modulation of this logarithmic term reveals new
types of asymetrical shapes, implying a… More >
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