Qingyue Zhao¹, Qiaoyu Gu², Zhijun Gao^3,*, Shipian Shao¹, Xinyuan Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1773-1788, 2023, DOI:10.32604/cmes.2023.027500 - 26 June 2023

Abstract Building indoor dangerous behavior recognition is a specific application in the field of abnormal human recognition. A human dangerous behavior recognition method based on LSTM-GCN with attention mechanism (GLA) model was proposed aiming at the problem that the existing human skeleton-based action recognition methods cannot fully extract the temporal and spatial features. The network connects GCN and LSTM network in series, and inputs the skeleton sequence extracted by GCN that contains spatial information into the LSTM layer for time sequence feature extraction, which fully excavates the temporal and spatial features of the skeleton sequence. Finally, More >

Xudong Jiang¹, Chang Liu^1,2,*, Shaohui Zhang³, Weisheng Zhang^1,2, Zongliang Du^1,2, Xiaoyu Zhang³, Huizhong Zeng³, Xu Guo^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 809-838, 2023, DOI:10.32604/cmes.2023.023561 - 27 October 2022

Abstract This paper proposes an explicit method for topology optimization of stiffened plate structures. The present work is devoted to simultaneously optimizing stiffeners’ shape, size and layout by seeking the optimal geometry parameters of a series of moving morphable components (MMC). The stiffeners with straight skeletons and the stiffeners with curved skeletons are considered to enhance the modeling and optimization capability of the current approach. All the stiffeners are represented under the Lagrangian-description framework in a fully explicit way, and the adaptive ground structure method, as well as dynamically updated plate/shell elements, is used to obtain More > Graphic Abstract

Long Chen^1,*, Shuxun Liang², Nan Yan², Xiangqian Yang², Baotong Li³

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 687-709, 2023, DOI:10.32604/cmes.2022.021986 - 29 September 2022

Abstract Lattice structures with excellent physical properties have attracted great research interest. In this paper, a novel volume parametric modeling method based on the skeleton model is proposed for the construction of three-dimensional lattice structures. The skeleton model is divided into three types of nodes. And the corresponding algorithms are utilized to construct diverse types of volume parametric nodes. The unit-cell is assembled with distinct nodes according to the geometric features. The final lattice structure is created by the periodic arrangement of unit-cells. Several different types of volume parametric lattice structures are constructed to prove the More > Graphic Abstract

Motasem S. Alsawadi^1,*, El-Sayed M. El-kenawy^2,3, Miguel Rio¹

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 19-36, 2023, DOI:10.32604/cmc.2023.032499 - 22 September 2022

Abstract The ever-growing available visual data (i.e., uploaded videos and pictures by internet users) has attracted the research community's attention in the computer vision field. Therefore, finding efficient solutions to extract knowledge from these sources is imperative. Recently, the BlazePose system has been released for skeleton extraction from images oriented to mobile devices. With this skeleton graph representation in place, a Spatial-Temporal Graph Convolutional Network can be implemented to predict the action. We hypothesize that just by changing the skeleton input data for a different set of joints that offers more information about the action of More >

LAURA LAFON-HUGHES^1,2,*

BIOCELL, Vol.46, No.12, pp. 2531-2535, 2022, DOI:10.32604/biocell.2022.022713 - 10 August 2022

Abstract Poly(ADP-ribose) (PAR) is a highly negatively charged polymer. PAR is synthesized by poly(ADP-ribose)polymerases (PARPs) and is involved in the assembly and stabilization of macromolecular complexes. Here, the presence and putative roles of poly(ADP-ribosyl)ation (PARylation) associated to adherens junctions (AJ) and the actin cytoskeleton in epithelial and Schwann cells, is reviewed. The hypothesis generated by analogy, stating that PAR is associated to AJ in other cell types, is postulated. According to this hypothesis, PAR associated to puncta adherentia in chemical synapses would participate in plasticity, learning and memory. In turn, PAR associated to fascia adherens in cardiomyocytes, would affect More >

Jiabao Shi¹, Zhao Qiu^1,*, Tao Chen¹, Jiale Lin¹, Hancheng Huang², Yunlong He³, Yu Yang³

Journal of New Media, Vol.4, No.2, pp. 97-106, 2022, DOI:10.32604/jnm.2022.027176 - 13 June 2022

Abstract Big data is a comprehensive result of the development of the Internet of Things and information systems. Computer vision requires a lot of data as the basis for research. Because skeleton data can adapt well to dynamic environment and complex background, it is used in action recognition tasks. In recent years, skeleton-based action recognition has received more and more attention in the field of computer vision. Therefore, the keypoints of human skeletons are essential for describing the pose estimation of human and predicting the action recognition of the human. This paper proposes a skeleton point More >

DANILA BOBKOV^1,2,3,*, ANASTASIA POLYANSKAYA¹, ANASTASIA MUSORINA¹, GALINA POLJANSKAYA¹

BIOCELL, Vol.46, No.9, pp. 2053-2058, 2022, DOI:10.32604/biocell.2022.019469 - 18 May 2022

Abstract All non-immortalized mesenchymal stem cells have a limited proliferative potential, that is, replicative senescence (RS) is an integral characteristic of the life of all mesenchymal stem cells (MSCs). It is known that one of the important signs of RS is a decrease of cell motility, and that violations of migration processes contribute to the deterioration of tissue regeneration. Therefore, the characterization of the properties of the cell line associated with RS is a prerequisite for the effective use of MSCs in restorative medicine. One of the key proteins regulating cell motility is the small GTPase More >

JULIANA SOARES^1,2,#, DOUGLAS G. FREITAS^1,3,#, PEDRO S. LOURENÇO^1,4, JEFTE FARIAS^1,5, BRUNO PONTES^1,2,3,4,5,*

BIOCELL, Vol.46, No.9, pp. 2009-2013, 2022, DOI:10.32604/biocell.2022.019969 - 18 May 2022

Abstract Mammalian cell surfaces consist of the plasma membrane supported by an underneath cortical cytoskeleton. Together, these structures can control not only the shape of cells but also a series of cellular functions ranging from migration and division to exocytosis, endocytosis and differentiation. Furthermore, the cell surface is capable of exerting and reacting to mechanical forces. Its viscoelastic properties, especially membrane tension and bending modulus, are fundamental parameters involved in these responses. This viewpoint summarizes our current knowledge on how to measure the viscoelastic properties of cell surfaces employing optical tweezers-based tether assays, paving the way More >

Hyun Yoo¹, Kyungyong Chung^2,*

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 1-13, 2022, DOI:10.32604/iasc.2022.024890 - 15 April 2022

Abstract Human pose estimation has been a major concern in the field of computer vision. The existing method for recognizing human motion based on two-dimensional (2D) images showed a low recognition rate owing to motion depth, interference between objects, and overlapping problems. A convolutional neural network (CNN) based algorithm recently showed improved results in the field of human skeleton detection. In this study, we have combined human skeleton detection and deep neural network (DNN) to classify the motion of the human body. We used the visual geometry group network (VGGNet) CNN for human skeleton detection, and More >

Batyrkhan Omarov^1,2,3,4,*, Sergazy Narynov¹, Zhandos Zhumanov^1,2, Aidana Gumar^1,5, Mariyam Khassanova^1,5

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 315-331, 2022, DOI:10.32604/cmc.2022.024566 - 24 February 2022

Abstract In this paper, we propose a skeleton-based method to identify violence and aggressive behavior. The approach does not necessitate high-processing equipment and it can be quickly implemented. Our approach consists of two phases: feature extraction from image sequences to assess a human posture, followed by activity classification applying a neural network to identify whether the frames include aggressive situations and violence. A video violence dataset of 400 min comprising a single person's activities and 20 h of video data including physical violence and aggressive acts, and 13 classifications for distinguishing aggressor and victim behavior were More >