Yanjun Zhang¹, Yongqiang He², Jingbo Zhang¹, Yaru Zhao³, Zhihua Cui^1,*, Wensheng Zhang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 363-383, 2023, DOI:10.32604/cmes.2023.025832 - 23 April 2023

Abstract The video compression sensing method based on multi hypothesis has attracted extensive attention in the research of video codec with limited resources. However, the formation of high-quality prediction blocks in the multi hypothesis prediction stage is a challenging task. To resolve this problem, this paper constructs a novel compressed sensing-based high-quality adaptive video reconstruction optimization method. It mainly includes the optimization of prediction blocks (OPBS), the selection of search windows and the use of neighborhood information. Specifically, the OPBS consists of two parts: the selection of blocks and the optimization of prediction blocks. We combine… More >

Weiguang Zheng^1,2,3, Junzhu Zhang^1,2, Shanchao Wang^2,*, Gaoshan Feng², Xiaohong Xu², Qiuxiang Ma²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 489-508, 2023, DOI:10.32604/cmes.2023.025169 - 23 April 2023

Abstract The extended Kalman filter (EKF) algorithm and acceleration sensor measurements were used to identify vehicle mass and road gradient in the work. Four different states of fixed mass, variable mass, fixed slope and variable slope were set to simulate real-time working conditions, respectively. A comprehensive electric commercial vehicle shifting strategy was formulated according to the identification results. The co-simulation results showed that, compared with the recursive least square (RLS) algorithm, the proposed algorithm could identify the real-time vehicle mass and road gradient quickly and accurately. The comprehensive shifting strategy formulated had the following advantages, e.g., More > Graphic Abstract

Jian Kang¹, Wanshu Fan¹, Yijing Li², Rui Liu¹, Dongsheng Zhou^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 607-629, 2023, DOI:10.32604/cmes.2023.024420 - 23 April 2023

Abstract With the advancement of image sensing technology, estimating 3D human pose from monocular video has become a hot research topic in computer vision. 3D human pose estimation is an essential prerequisite for subsequent action analysis and understanding. It empowers a wide spectrum of potential applications in various areas, such as intelligent transportation, human-computer interaction, and medical rehabilitation. Currently, some methods for 3D human pose estimation in monocular video employ temporal convolutional network (TCN) to extract inter-frame feature relationships, but the majority of them suffer from insufficient inter-frame feature relationship extractions. In this paper, we decompose… More >

Adnan Malik¹, Muhammad Ali¹, Faisal S. Alsubaei², Nisar Ahmed^3,*, Harish Kumar⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 965-999, 2023, DOI:10.32604/cmes.2023.022493 - 23 April 2023

Abstract The security of digital images transmitted via the Internet or other public media is of the utmost importance. Image encryption is a method of keeping an image secure while it travels across a non-secure communication medium where it could be intercepted by unauthorized entities. This study provides an approach to color image encryption that could find practical use in various contexts. The proposed method, which combines four chaotic systems, employs singular value decomposition and a chaotic sequence, making it both secure and compression-friendly. The unified average change intensity, the number of pixels’ change rate, information More >

Yingjun Wang^1,*, Xinqing Li¹, Kai Long², Peng Wei³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 1-34, 2023, DOI:10.32604/cmes.2023.027603 - 23 April 2023

Abstract Topology optimization (TO), a numerical technique to find the optimal material layout with a given design domain, has attracted interest from researchers in the field of structural optimization in recent years. For beginners, opensource codes are undoubtedly the best alternative to learning TO, which can elaborate the implementation of a method in detail and easily engage more people to employ and extend the method. In this paper, we present a summary of various open-source codes and related literature on TO methods, including solid isotropic material with penalization (SIMP), evolutionary method, level set method (LSM), moving More > Graphic Abstract

M. C. Shanmukha¹, Sokjoon Lee^2,*, A. Usha³, K. C. Shilpa⁴, Muhammad Azeem⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 939-964, 2023, DOI:10.32604/cmes.2023.027254 - 23 April 2023

Abstract Graph theory plays a significant role in the applications of chemistry, pharmacy, communication, maps, and aeronautical fields. The molecules of chemical compounds are modelled as a graph to study the properties of the compounds. The geometric structure of the compound relates to a few physical properties such as boiling point, enthalpy, π-electron energy, molecular weight. The article aims to determine the practical application of graph theory by solving one of the interdisciplinary problems describing the structures of benzenoid hydrocarbons and graphenylene. The topological index is an invariant of a molecular graph associated with the chemical More >

Xiaoyan Jiang^1,2, Zuojin Hu¹, Shuihua Wang², Yudong Zhang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 35-82, 2023, DOI:10.32604/cmes.2023.027676 - 23 April 2023

Abstract Over the years, the continuous development of new technology has promoted research in the field of posture recognition and also made the application field of posture recognition have been greatly expanded. The purpose of this paper is to introduce the latest methods of posture recognition and review the various techniques and algorithms of posture recognition in recent years, such as scale-invariant feature transform, histogram of oriented gradients, support vector machine (SVM), Gaussian mixture model, dynamic time warping, hidden Markov model (HMM), lightweight network, convolutional neural network (CNN). We also investigate improved methods of CNN, such… More >

Joseph Bamidele Awotunde¹, Sanjay Misra^2,*, Vikash Katta², Oluwafemi Charles Adebayo¹

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 131-154, 2023, DOI:10.32604/cmes.2023.026812 - 23 April 2023

Abstract The task of classifying opinions conveyed in any form of text online is referred to as sentiment analysis. The emergence of social media usage and its spread has given room for sentiment analysis in our daily lives. Social media applications and websites have become the foremost spring of data recycled for reviews for sentimentality in various fields. Various subject matter can be encountered on social media platforms, such as movie product reviews, consumer opinions, and testimonies, among others, which can be used for sentiment analysis. The rapid uncovering of these web contents contains divergence of… More >

Jianfang Qi¹, Yue Li^1,3, Haibin Jin¹, Jianying Feng¹, Dong Tian¹, Weisong Mu^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 197-232, 2023, DOI:10.32604/cmes.2023.026113 - 23 April 2023

Abstract An appropriate optimal number of market segments (ONS) estimation is essential for an enterprise to achieve successful market segmentation, but at present, there is a serious lack of attention to this issue in market segmentation. In our study, an independent adaptive ONS estimation method BWCON-NSDK-means++ is proposed by integrating a new internal validity index (IVI) Between-Within-Connectivity (BWCON) and a new stable clustering algorithm Natural-SDK-means++ (NSDK-means++) in a novel way. First, to complete the evaluation dimensions of the existing IVIs, we designed a connectivity formula based on the neighbor relationship and proposed the BWCON by integrating… More >

Shayla Islam¹, Anil Kumar Budati^1,*, Mohammad Kamrul Hasan², Saoucene Mahfoudh³, Syed Bilal Hussian Shah³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 813-825, 2023, DOI:10.32604/cmes.2023.027595 - 23 April 2023

Abstract In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promising approach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio (SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambient Radio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum for the transmission of data without loss or without collision at a specific time. In this paper, the authors proposed a novel Spectrum Sensing (SS) detection technique in the Cognitive… More >