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  • Open Access

    ARTICLE

    BCCLR: A Skeleton-Based Action Recognition with Graph Convolutional Network Combining Behavior Dependence and Context Clues

    Yunhe Wang1, Yuxin Xia2, Shuai Liu2,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4489-4507, 2024, DOI:10.32604/cmc.2024.048813

    Abstract In recent years, skeleton-based action recognition has made great achievements in Computer Vision. A graph convolutional network (GCN) is effective for action recognition, modelling the human skeleton as a spatio-temporal graph. Most GCNs define the graph topology by physical relations of the human joints. However, this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs, resulting in a low recognition rate for specific actions with implicit correlation between joint pairs. In addition, existing methods ignore the trend correlation between adjacent frames within an action and context clues, leading to… More >

  • Open Access

    ARTICLE

    CL2ES-KDBC: A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

    Talal Albalawi, P. Ganeshkumar*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3511-3528, 2024, DOI:10.32604/cmc.2024.046396

    Abstract The Internet of Things (IoT) is a growing technology that allows the sharing of data with other devices across wireless networks. Specifically, IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks. In this framework, a Covariance Linear Learning Embedding Selection (CL2ES) methodology is used at first to extract the features highly associated with the IoT intrusions. Then, the Kernel Distributed Bayes Classifier (KDBC) is created to forecast attacks based on the probability distribution value precisely. In addition, a… More >

  • Open Access

    ARTICLE

    SATURATED AND SUBCOOLED POOL BOILING OF HFE-7200 MIXTURES ON A COPPER NANOWIRE SURFACE

    Aravind Sathyanarayanaa, Pramod Warrierb, Yogendra Joshia,*, Amyn Tejab

    Frontiers in Heat and Mass Transfer, Vol.2, No.4, pp. 1-7, 2011, DOI:10.5098/hmt.v2.4.3007

    Abstract Electrical and chemical compatibility requirements of electronic components pose significant constraints on the choice of liquid coolants. Dielectric coolants such as Novec fluids and fluoroinerts are plagued by poor thermal properties. This necessitates the development of new heat transfer fluids. In this study we examine mixture formulations that provide an avenue for enhancing the properties of existing heat transfer fluids. Mixture formulations of Novec fluid (HFE 7200) with Methanol and Ethoxybutane are considered. Pool boiling experiments are performed on a copper nanowire surface. The results show an improvement of 24% and 11% in the CHF of HFE 7200 – Methanol… More >

  • Open Access

    REVIEW

    ONSET OF NUCLEATE BOILING IN MINI AND MICROCHANNELS: A BRIEF REVIEW

    Tomio Okawa*,†

    Frontiers in Heat and Mass Transfer, Vol.3, No.1, pp. 1-8, 2012, DOI:10.5098/hmt.v3.1.3001

    Abstract The present article summarizes the studies on the thermalhydraulic condition under which the onset of nucleate boiling (ONB) is triggered in subcooled flow boiling. Available correlations and experimental data show that the ONB is tended to be delayed in mini and microchannels. It is known that the ONB condition is significantly dependent on the surface condition even in conventional-sized channels. Accumulation of ONB data accompanied by the information on the surface condition is therefore considered of importance to elucidate the mechanisms of boiling incipience in microchannels. Discussion is also made for the bubble dynamics observed in mini and microchannels. It… More >

  • Open Access

    ARTICLE

    Low-molecular-weight fucoidan inhibits the proliferation of melanoma via Bcl-2 phosphorylation and PTEN/AKT pathway

    MINJI PARK1, CHULHWAN BANG2, WON-SOO YUN3, YUN-MI JEONG3,*

    Oncology Research, Vol.32, No.2, pp. 273-282, 2024, DOI:10.32604/or.2023.044362

    Abstract Fucoidan, a sulfate polysaccharide obtained from brown seaweed, has various bioactive properties, including anti-inflammatory, anti-cancer, anti-viral, anti-oxidant, anti-coagulant, anti-thrombotic, anti-angiogenic, and anti-Helicobacter pylori properties. However, the effects of low-molecular-weight fucoidan (LMW-F) on melanoma cell lines and three dimensional (3D) cell culture models are not well understood. This study aimed to investigate the effects of LMW-F on A375 human melanoma cells and cryopreserved biospecimens derived from patients with advanced melanoma. Ultrasonic wave was used to fragment fucoidan derived from Fucus vesiculosus into smaller LMW-F. MTT and live/dead assays showed that LMW-F inhibited cell proliferation in both A375 cells and patient-derived melanoma… More >

  • Open Access

    ARTICLE

    An Optimized System of Random Forest Model by Global Harmony Search with Generalized Opposition-Based Learning for Forecasting TBM Advance Rate

    Yingui Qiu1, Shuai Huang1, Danial Jahed Armaghani2, Biswajeet Pradhan3, Annan Zhou4, Jian Zhou1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2873-2897, 2024, DOI:10.32604/cmes.2023.029938

    Abstract As massive underground projects have become popular in dense urban cities, a problem has arisen: which model predicts the best for Tunnel Boring Machine (TBM) performance in these tunneling projects? However, performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers. On the other hand, a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule. The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications. The previously-proposed intelligent techniques in this field are mostly based on a… More >

  • Open Access

    ARTICLE

    An Improved Lung Cancer Segmentation Based on Nature-Inspired Optimization Approaches

    Shazia Shamas1, Surya Narayan Panda1,*, Ishu Sharma1,*, Kalpna Guleria1, Aman Singh2,3,4, Ahmad Ali AlZubi5, Mallak Ahmad AlZubi6

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1051-1075, 2024, DOI:10.32604/cmes.2023.030712

    Abstract The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis and planning intervention. This research work addresses the major issues pertaining to the field of medical image processing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposes an improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. The better resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In this process, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarm intelligent techniques. The techniques… More >

  • Open Access

    ARTICLE

    Classification of Human Protein in Multiple Cells Microscopy Images Using CNN

    Lina Al-joudi, Muhammad Arif*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1763-1780, 2023, DOI:10.32604/cmc.2023.039413

    Abstract The subcellular localization of human proteins is vital for understanding the structure of human cells. Proteins play a significant role within human cells, as many different groups of proteins are located in a specific location to perform a particular function. Understanding these functions will help in discovering many diseases and developing their treatments. The importance of imaging analysis techniques, specifically in proteomics research, is becoming more prevalent. Despite recent advances in deep learning techniques for analyzing microscopy images, classification models have faced critical challenges in achieving high performance. Most protein subcellular images have a significant class imbalance. We use oversampling… More >

  • Open Access

    ARTICLE

    Developing a Breast Cancer Resistance Protein Substrate Prediction System Using Deep Features and LDA

    Mehdi Hassan1,2, Safdar Ali3, Jin Young Kim2,*, Muhammad Sanaullah4, Hani Alquhayz5, Khushbakht Safdar6

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1643-1663, 2023, DOI:10.32604/cmc.2023.038578

    Abstract Breast cancer resistance protein (BCRP) is an important resistance protein that significantly impacts anticancer drug discovery, treatment, and rehabilitation. Early identification of BCRP substrates is quite a challenging task. This study aims to predict early substrate structure, which can help to optimize anticancer drug development and clinical diagnosis. For this study, a novel intelligent approach-based methodology is developed by modifying the ResNet101 model using transfer learning (TL) for automatic deep feature (DF) extraction followed by classification with linear discriminant analysis algorithm (TLRNDF-LDA). This study utilized structural fingerprints, which are exploited by DF contrary to conventional molecular descriptors. The proposed in… More >

  • Open Access

    PROCEEDINGS

    The Correlation Between the Cyclic Oxidation Behavior of EB-PVD TBC and Refurbishment Process

    Pan Li1, Xiaochao Jin1, Pin Lv1, Xueling Fan1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.010540

    Abstract Refurbishment of thermal barrier coating (TBC) has become a valuable technique to prolong the service life of high-temperature components. In this work, the effect of refurbishment process on the oxidation behaviors of TBC was investigated. Before recoating, the soft chemical stripping method was used to remove TBC from DD6 single-crystal superalloy. The results showed that a certain amount of IDZ layer with Cr-rich would be retained in the DD6 superalloy substrate after coating removal. The characteristics of the β phases change from the elongated grain shapes and a high aspect ratio in the ordinary specimens to the equiaxed shape in… More >

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